CN115454181A - Internet of things-based intelligent monitoring method and system for agricultural greenhouse - Google Patents
Internet of things-based intelligent monitoring method and system for agricultural greenhouse Download PDFInfo
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- CN115454181A CN115454181A CN202211221074.9A CN202211221074A CN115454181A CN 115454181 A CN115454181 A CN 115454181A CN 202211221074 A CN202211221074 A CN 202211221074A CN 115454181 A CN115454181 A CN 115454181A
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Abstract
The invention relates to the technical field of agricultural greenhouses, and particularly discloses an intelligent monitoring method and system for an agricultural greenhouse based on the Internet of things. According to the invention, a plurality of agricultural target images are periodically extracted by carrying out real-time monitoring shooting in an agricultural greenhouse; performing stage analysis on the plurality of agricultural target images to generate stage analysis results; planning a basic induction period and carrying out periodic induction monitoring; performing real-time activity analysis and identifying the type of agricultural activity; the basic sensing period is adjusted. The intelligent monitoring system has the advantages that real-time monitoring shooting can be carried out, a plurality of agricultural target images are extracted, stage analysis and identification are carried out, corresponding basic induction periods are planned, induction monitoring is carried out according to the basic induction periods, agricultural activity judgment and identification are carried out, adaptability adjustment is carried out on the basic induction periods, the frequency of induction monitoring is kept to be adaptive to the growth of agricultural targets in the agricultural greenhouse, long-time working of intelligent monitoring equipment is not needed, energy is saved, and damage to the intelligent monitoring equipment can be avoided.
Description
Technical Field
The invention belongs to the technical field of agricultural greenhouses, and particularly relates to an intelligent monitoring method and system for an agricultural greenhouse based on the Internet of things.
Background
Agricultural greenhouses, also known as greenhouses, are light-transmitting and heat-insulating facilities for cultivating plants. In seasons unsuitable for plant growth, the method can provide the growth period of the greenhouse and increase the yield, and is mainly used for cultivating or raising seedlings of plants like warm vegetables, flowers and trees in low-temperature seasons. The types of greenhouses are various, and the greenhouses can be divided into a great number according to different roof truss materials, lighting materials, shapes, heating conditions and the like. The types of the greenhouse comprise a planting greenhouse, a breeding greenhouse, an exhibition greenhouse, an experiment greenhouse, a catering greenhouse, an entertainment greenhouse and the like; the greenhouse system comprises a heating system, a heat preservation system, a cooling system, a ventilation system, a control system, an irrigation system and the like.
The agricultural greenhouse needs to be monitored in various aspects such as video monitoring, air temperature and humidity monitoring, soil temperature and humidity monitoring, illumination monitoring and the like, so that various intelligent monitoring devices are needed to work. In the prior art, various intelligent monitoring devices are generally kept to be monitored on line all the time, real-time monitoring data are provided, although the monitoring method can effectively realize environment monitoring of the agricultural greenhouse, continuous on-line monitoring not only wastes energy, but also easily causes damage to the intelligent monitoring devices due to long-time work, and accordingly corresponding monitoring functions are lost within the damage time of the intelligent monitoring devices.
Disclosure of Invention
The embodiment of the invention aims to provide an intelligent monitoring method and system for an agricultural greenhouse based on the Internet of things, and aims to solve the problems in the background art.
In order to achieve the above purpose, the embodiments of the present invention provide the following technical solutions:
an intelligent monitoring method for an agricultural greenhouse based on the Internet of things specifically comprises the following steps:
carrying out real-time monitoring shooting in an agricultural greenhouse to generate a monitoring shooting video, carrying out agricultural product analysis, and periodically extracting a plurality of agricultural target images;
acquiring stage image information corresponding to agricultural products, and performing stage analysis on a plurality of agricultural target images to generate stage analysis results;
planning a basic induction period according to the stage analysis result, and carrying out induction monitoring on the environmental data of the agricultural greenhouse according to the basic induction period;
performing real-time activity analysis on the monitoring shooting video, judging whether agricultural activities exist or not, and identifying the types of the agricultural activities when the agricultural activities exist;
and adjusting the basic induction period according to the agricultural activity type to generate an adjustment induction period, determining an adjustment time period, and performing induction monitoring on the environmental data of the agricultural greenhouse according to the adjustment induction period in the adjustment time period.
As a further limitation of the technical solution of the embodiment of the present invention, the performing real-time monitoring shooting in an agricultural greenhouse to generate a monitoring shooting video, performing agricultural product analysis, and periodically extracting a plurality of agricultural target images specifically includes the following steps:
carrying out real-time monitoring shooting in an agricultural greenhouse to generate a monitoring shooting video;
performing frame-by-frame processing on the monitoring shooting video to obtain a plurality of monitoring shooting images;
randomly selecting a plurality of target shot images from the plurality of monitoring shot images;
and carrying out agricultural product analysis on the plurality of target shooting images, and periodically extracting a plurality of agricultural target images.
As a further limitation of the technical solution of the embodiment of the present invention, the step of obtaining phase image information corresponding to an agricultural product target, and performing phase analysis on a plurality of agricultural target images, wherein the step of generating a phase analysis result specifically includes the following steps:
carrying out target identification according to the plurality of agricultural target images to obtain agricultural target information;
acquiring corresponding stage image information according to the agricultural target information;
and performing stage analysis and identification on the plurality of agricultural target images according to the stage image information to generate a stage analysis result.
As a further limitation of the technical solution of the embodiment of the present invention, the planning a basic sensing period according to the stage analysis result, and performing sensing monitoring on the environmental data of the agricultural greenhouse according to the basic sensing period specifically includes the following steps:
planning a basic induction cycle according to the stage analysis result;
generating induction monitoring signals periodically according to the basic induction period;
and carrying out induction monitoring on the environmental data of the agricultural greenhouse according to the induction monitoring signal.
As a further limitation of the technical solution of the embodiment of the present invention, the performing real-time activity analysis on the monitoring shot video, determining whether agricultural activities exist, and identifying the agricultural activity type when the agricultural activities exist specifically includes the following steps:
performing real-time activity analysis on the monitoring shooting video to generate an activity analysis result;
judging whether agricultural activities exist or not according to the activity analysis result;
when agricultural activities exist, intercepting corresponding activity shooting videos;
and performing activity recognition analysis according to the activity shooting video to determine the type of the agricultural activity.
As a further limitation of the technical solution of the embodiment of the present invention, the adjusting the basic sensing period according to the type of the agricultural activity to generate an adjusted sensing period and determine an adjusted time period, and the sensing and monitoring the environmental data of the agricultural greenhouse according to the adjusted sensing period in the adjusted time period specifically includes the following steps:
performing periodic adjustment analysis according to the agricultural activity type to generate adjustment guide information;
adjusting the basic induction period according to the adjustment guide information to generate an adjustment induction period and determine an adjustment time period;
periodically generating an induction monitoring signal according to the adjustment induction period in the adjustment time period;
and carrying out induction monitoring on the environmental data of the agricultural greenhouse according to the induction monitoring signal.
The utility model provides an agricultural greenhouse intelligent monitoring system based on thing networking, the system shoots processing unit, target stage analysis unit, basic response monitoring unit, activity analysis recognition unit and regulation response monitoring unit including the control, wherein:
the monitoring shooting processing unit is used for carrying out real-time monitoring shooting in the agricultural greenhouse, generating a monitoring shooting video, carrying out agricultural product analysis and periodically extracting a plurality of agricultural target images;
the target stage analysis unit is used for acquiring stage image information corresponding to agricultural products, performing stage analysis on a plurality of agricultural target images and generating stage analysis results;
the basic induction monitoring unit is used for planning a basic induction period according to the stage analysis result and carrying out induction monitoring on the environmental data of the agricultural greenhouse according to the basic induction period;
the activity analysis and identification unit is used for carrying out real-time activity analysis on the monitoring shooting video, judging whether agricultural activities exist or not, and identifying the types of the agricultural activities when the agricultural activities exist;
and the adjusting induction monitoring unit is used for adjusting the basic induction period according to the agricultural activity type, generating an adjusting induction period, determining an adjusting time period, and performing induction monitoring on the environmental data of the agricultural greenhouse according to the adjusting induction period in the adjusting time period.
As a further limitation of the technical solution of the embodiment of the present invention, the monitoring shooting processing unit specifically includes:
the monitoring shooting module is used for carrying out real-time monitoring shooting in the agricultural greenhouse to generate a monitoring shooting video;
the frame-by-frame processing module is used for carrying out frame-by-frame processing on the monitoring shooting video to obtain a plurality of monitoring shooting images;
the random selection module is used for randomly selecting a plurality of target shooting images from a plurality of monitoring shooting images;
and the image extraction module is used for carrying out agricultural product analysis on the plurality of target shooting images and periodically extracting a plurality of agricultural target images.
As a further limitation of the technical solution of the embodiment of the present invention, the target stage analysis unit specifically includes:
the target identification module is used for carrying out target identification according to the agricultural target images to obtain agricultural target information;
the information acquisition module is used for acquiring corresponding stage image information according to the agricultural target information;
and the stage analysis module is used for carrying out stage analysis and identification on the plurality of agricultural target images according to the stage image information to generate a stage analysis result.
As a further limitation of the technical solution of the embodiment of the present invention, the basic sensing and monitoring unit specifically includes:
the period planning module is used for planning a basic induction period according to the stage analysis result;
the signal generation module is used for periodically generating induction monitoring signals according to the basic induction period;
and the sensing monitoring module is used for sensing and monitoring the environmental data of the agricultural greenhouse according to the sensing and monitoring signal.
Compared with the prior art, the invention has the beneficial effects that:
according to the embodiment of the invention, a plurality of agricultural target images are periodically extracted by carrying out real-time monitoring shooting in an agricultural greenhouse; performing stage analysis on the plurality of agricultural target images to generate stage analysis results; planning a basic induction period and carrying out periodic induction monitoring; performing real-time activity analysis and identifying the type of agricultural activity; the base induction period is adjusted. The intelligent monitoring system has the advantages that real-time monitoring shooting can be carried out, a plurality of agricultural target images are extracted, stage analysis and identification are carried out, corresponding basic induction periods are planned, induction monitoring is carried out according to the basic induction periods, agricultural activity judgment and identification are carried out, adaptability adjustment is carried out on the basic induction periods, the frequency of induction monitoring is kept to be adaptive to the growth of agricultural targets in the agricultural greenhouse, long-time working of intelligent monitoring equipment is not needed, energy is saved, and damage to the intelligent monitoring equipment can be avoided.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention.
Fig. 1 shows a flow chart of a method provided by an embodiment of the invention.
Fig. 2 shows a flowchart of monitoring shooting target extraction in the method provided by the embodiment of the invention.
Fig. 3 is a flowchart illustrating an analysis result of a generation phase in the method according to the embodiment of the present invention.
Fig. 4 shows a flowchart of basic cycle sensing monitoring in the method provided by the embodiment of the present invention.
Fig. 5 shows a flow chart of identifying the type of agricultural activity in the method provided by the embodiment of the invention.
Fig. 6 shows a flow chart of adjusting periodic inductive monitoring in a method provided by an embodiment of the present invention.
Fig. 7 shows an application architecture diagram of a system provided by an embodiment of the invention.
Fig. 8 is a block diagram showing a configuration of a monitoring shooting processing unit in the system according to the embodiment of the present invention.
Fig. 9 shows a block diagram of a target phase analysis unit in the system according to the embodiment of the present invention.
Fig. 10 shows a block diagram of a basic sensing and monitoring unit in the system according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It can be understood that in the agricultural greenhouse in the prior art, various intelligent monitoring devices are generally kept to be monitored on line all the time, real-time monitoring data are provided, and although the monitoring method can effectively realize the environmental monitoring of the agricultural greenhouse, the on-line monitoring all the time not only wastes energy, but also easily causes the damage of the intelligent monitoring devices due to long-time work, so that the corresponding monitoring function is lost in the time when the intelligent monitoring devices are damaged.
In order to solve the problems, the embodiment of the invention periodically extracts a plurality of agricultural target images by carrying out real-time monitoring shooting in an agricultural greenhouse; performing stage analysis on the plurality of agricultural target images to generate stage analysis results; planning a basic induction period and carrying out periodic induction monitoring; performing real-time activity analysis and identifying the type of agricultural activity; the basic sensing period is adjusted. The intelligent monitoring system has the advantages that real-time monitoring shooting can be carried out, a plurality of agricultural target images are extracted, stage analysis and identification are carried out, corresponding basic induction periods are planned, induction monitoring is carried out according to the basic induction periods, agricultural activity judgment and identification are carried out, adaptability adjustment is carried out on the basic induction periods, the frequency of induction monitoring is kept to be adaptive to the growth of agricultural targets in the agricultural greenhouse, long-time working of intelligent monitoring equipment is not needed, energy is saved, and damage to the intelligent monitoring equipment can be avoided.
Fig. 1 shows a flow chart of a method provided by an embodiment of the invention.
Specifically, the intelligent monitoring method for the agricultural greenhouse based on the Internet of things comprises the following steps:
and S101, carrying out real-time monitoring shooting in the agricultural greenhouse, generating a monitoring shooting video, carrying out agricultural product analysis, and periodically extracting a plurality of agricultural target images.
In the embodiment of the invention, real-time monitoring shooting is carried out at a plurality of positions in an agricultural greenhouse to generate a monitoring shooting video, a plurality of monitoring shooting images are obtained by carrying out frame-by-frame processing on the monitoring shooting video, a plurality of target shooting images are periodically and randomly selected from the plurality of monitoring shooting images according to a preset monitoring shooting processing period, a background in the target shooting images is distinguished from agricultural products by analyzing the plurality of target shooting images, the agricultural products in the plurality of target shooting images are identified, and a plurality of agricultural target images are extracted from the plurality of target shooting images.
Specifically, fig. 2 shows a flowchart of monitoring shooting target extraction in the method provided by the embodiment of the present invention.
In a preferred embodiment provided by the present invention, the performing real-time monitoring shooting in an agricultural greenhouse, generating a monitoring shooting video, performing agricultural product analysis, and periodically extracting a plurality of agricultural target images specifically includes the following steps:
and step S1011, carrying out real-time monitoring shooting in the agricultural greenhouse to generate a monitoring shooting video.
Step S1012, performing frame-by-frame processing on the monitoring shot video to obtain a plurality of monitoring shot images.
In step S1013, a plurality of target captured images are randomly selected from the plurality of monitoring captured images.
And step S1014, carrying out agricultural product analysis on the plurality of target shooting images, and periodically extracting a plurality of agricultural target images.
Further, the intelligent monitoring method for the agricultural greenhouse based on the Internet of things further comprises the following steps:
and S102, acquiring stage image information corresponding to agricultural products, and performing stage analysis on a plurality of agricultural target images to generate stage analysis results.
In the embodiment of the invention, the characteristics of a plurality of agricultural target images are analyzed, the types of agricultural targets are identified according to the characteristics, after the type identification is completed, agricultural target information is obtained, the stage image information of the type of crops is matched from a database of a system according to the agricultural target information, the plurality of agricultural target images are compared and analyzed by taking the stage image information as a standard, the growth stages of the corresponding crops in the agricultural greenhouse are determined, and a stage analysis result is generated.
Specifically, fig. 3 shows a flowchart of a generation phase analysis result in the method provided in the embodiment of the present invention.
In a preferred embodiment of the present invention, the obtaining phase image information corresponding to an agricultural product target, and performing phase analysis on a plurality of agricultural target images, and generating a phase analysis result specifically includes the following steps:
and S1021, performing target identification according to the plurality of agricultural target images to obtain agricultural target information.
Step S1022, acquiring corresponding stage image information according to the agricultural target information.
And S1023, performing stage analysis and identification on the plurality of agricultural target images according to the stage image information to generate stage analysis results.
Further, the intelligent monitoring method for the agricultural greenhouse based on the Internet of things further comprises the following steps:
and S103, planning a basic induction period according to the stage analysis result, and carrying out induction monitoring on the environmental data of the agricultural greenhouse according to the basic induction period.
In the embodiment of the invention, a basic induction period corresponding to the variety and the growth stage of the crop is planned according to the stage analysis result, an induction monitoring signal is periodically generated on a corresponding time node according to the basic induction period, and further, the environment data of the agricultural greenhouse is periodically induction monitored according to the induction monitoring signal, wherein the induction monitoring includes environment temperature and humidity induction monitoring, soil temperature and humidity induction monitoring, illumination intensity induction monitoring and the like.
It can be understood that different sensing periods can be set for different types of crops (for example, for crops sensitive to the environment, high-frequency sensing monitoring is needed, so the sensing period is short; different induction periods can be set for crops of the same type at different growth stages (for example, at the bud stage, the crops are sensitive to the environment and need high-frequency induction monitoring, so the induction period is short, and at the mature stage, the crops are not sensitive to the environment and only need low-frequency induction monitoring, so the induction period is long).
Specifically, fig. 4 shows a flowchart of basic cycle sensing monitoring in the method provided in the embodiment of the present invention.
In a preferred embodiment of the present invention, the planning a basic sensing period according to the stage analysis result, and performing sensing monitoring on environmental data of an agricultural greenhouse according to the basic sensing period specifically includes the following steps:
and step S1031, planning a basic induction cycle according to the stage analysis result.
And S1032, periodically generating an induction monitoring signal according to the basic induction period.
And step S1033, performing induction monitoring on the environmental data of the agricultural greenhouse according to the induction monitoring signal.
Further, the intelligent monitoring method for the agricultural greenhouse based on the Internet of things further comprises the following steps:
and step S104, performing real-time activity analysis on the monitoring shooting video, judging whether agricultural activities exist, and identifying the agricultural activity types when the agricultural activities exist.
In the embodiment of the invention, the real-time activity analysis is carried out on the monitoring shooting video to generate an activity analysis result, whether agricultural activity exists in the agricultural greenhouse is judged in real time according to the activity analysis result, when the agricultural activity exists, the corresponding activity shooting video is intercepted, and the type of the agricultural activity in the agricultural greenhouse is determined by carrying out activity recognition analysis on the activity shooting video, wherein the specific type of the agricultural activity comprises the following steps: watering, fertilizing, turning soil and the like.
Specifically, fig. 5 shows a flowchart of identifying the agricultural activity type in the method provided by the embodiment of the invention.
In a preferred embodiment provided by the present invention, the performing real-time activity analysis on the monitoring shot video, determining whether there is an agricultural activity, and identifying the type of the agricultural activity when there is the agricultural activity specifically includes the following steps:
and S1041, performing real-time activity analysis on the monitoring shooting video to generate an activity analysis result.
And step S1042, judging whether agricultural activities exist according to the activity analysis result.
And S1043, when the agricultural activities exist, intercepting corresponding activity shooting videos.
And S1044, performing activity recognition analysis according to the activity shooting video and determining the type of the agricultural activity.
Further, the intelligent monitoring method for the agricultural greenhouse based on the Internet of things further comprises the following steps:
and S105, adjusting the basic induction cycle according to the agricultural activity type, generating an adjustment induction cycle, determining an adjustment time period, and performing induction monitoring on the environmental data of the agricultural greenhouse according to the adjustment induction cycle in the adjustment time period.
In the embodiment of the invention, the period regulation of the induction monitoring is analyzed according to the type of the agricultural activity to generate the regulation guide information, the basic induction period is regulated according to the regulation guide information to generate the regulation induction period, and the regulation time period is determined, so that after the agricultural activity, the induction monitoring signal is periodically generated according to the regulation induction period in the regulation time period, and the environment data of the agricultural greenhouse is periodically subjected to induction monitoring according to the corresponding induction monitoring signal.
It can be understood that after agricultural activities are carried out in the agricultural greenhouse, the corresponding environment may be changed drastically in a short time, so that the corresponding sensing monitoring period needs to be shortened for better monitoring the growth of crops, but for different agricultural activity types, different monitoring period adjustments can be carried out according to the influence degree of the agricultural activity types on the environment.
Specifically, fig. 6 shows a flowchart of adjusting the periodic sensing monitoring in the method according to the embodiment of the present invention.
In a preferred embodiment provided by the present invention, the adjusting the basic sensing period according to the type of the agricultural activity, generating an adjusted sensing period, and determining an adjusted time period, wherein the sensing and monitoring the environmental data of the agricultural greenhouse according to the adjusted sensing period in the adjusted time period specifically includes the following steps:
and S1051, performing periodic adjustment analysis according to the agricultural activity type to generate adjustment guidance information.
And step S1052, adjusting the basic induction period according to the adjustment guide information, generating an adjustment induction period, and determining an adjustment time period.
And S1053, periodically generating an induction monitoring signal according to the adjustment induction period in the adjustment time period.
And S1054, performing induction monitoring on the environmental data of the agricultural greenhouse according to the induction monitoring signal.
Further, fig. 7 is a diagram illustrating an application architecture of the system according to the embodiment of the present invention.
In another preferred embodiment provided by the present invention, an intelligent monitoring system for an agricultural greenhouse based on the internet of things includes:
and the monitoring shooting processing unit 101 is used for performing real-time monitoring shooting in the agricultural greenhouse, generating a monitoring shooting video, performing agricultural product analysis and periodically extracting a plurality of agricultural target images.
In the embodiment of the present invention, the monitoring shooting processing unit 101 performs real-time monitoring shooting at multiple positions in the agricultural greenhouse to generate a monitoring shooting video, performs frame-by-frame processing on the monitoring shooting video to obtain multiple monitoring shooting images, periodically and randomly selects multiple target shooting images from the multiple monitoring shooting images according to a preset monitoring shooting processing period, analyzes the multiple target shooting images, distinguishes a background in the target shooting images from agricultural products, identifies agricultural products in the multiple target shooting images, and extracts multiple agricultural target images from the multiple target shooting images.
Specifically, fig. 8 shows a block diagram of a monitoring shooting processing unit 101 in the system according to the embodiment of the present invention.
In an embodiment of the present invention, the monitoring shooting processing unit 101 specifically includes:
and the monitoring shooting module 1011 is used for carrying out real-time monitoring shooting in the agricultural greenhouse to generate a monitoring shooting video.
A frame-by-frame processing module 1012, configured to perform frame-by-frame processing on the monitoring shooting video to obtain a plurality of monitoring shooting images.
A random selecting module 1013 configured to randomly select a plurality of target captured images from the plurality of monitoring captured images.
And the image extraction module 1014 is used for performing agricultural product analysis on the plurality of target shooting images and periodically extracting a plurality of agricultural target images.
Further, agricultural greenhouse intelligent monitoring system based on thing networking still includes:
and the target stage analysis unit 102 is configured to acquire stage image information corresponding to an agricultural product, perform stage analysis on a plurality of agricultural target images, and generate a stage analysis result.
In the embodiment of the present invention, the target stage analysis unit 102 performs feature analysis on a plurality of agricultural target images, identifies the types of agricultural targets according to the feature analysis, obtains agricultural target information after completing the type identification, further matches stage image information of the type of crops from the database of the system according to the agricultural target information, further performs comparative analysis on the plurality of agricultural target images by using the stage image information as a standard, determines the growth stages of the corresponding crops in the agricultural greenhouse, and generates stage analysis results.
Specifically, fig. 9 shows a block diagram of a structure of the target phase analyzing unit 102 in the system according to the embodiment of the present invention.
In a preferred embodiment provided by the present invention, the target stage analysis unit 102 specifically includes:
and a target identification module 1021, configured to perform target identification according to the multiple agricultural target images to obtain agricultural target information.
The information obtaining module 1022 is configured to obtain corresponding stage image information according to the agricultural target information.
And the stage analysis module 1023 is used for performing stage analysis and identification on the plurality of agricultural target images according to the stage image information to generate a stage analysis result.
Further, agricultural greenhouse intelligent monitoring system based on thing networking still includes:
and the basic induction monitoring unit 103 is used for planning a basic induction period according to the stage analysis result and carrying out induction monitoring on the environmental data of the agricultural greenhouse according to the basic induction period.
In the embodiment of the present invention, the basic sensing and monitoring unit 103 plans a basic sensing period corresponding to the crop variety and the growth stage according to the stage analysis result, periodically generates a sensing and monitoring signal at a corresponding time node according to the basic sensing period, and further performs periodic sensing and monitoring on the environmental data of the agricultural greenhouse according to the sensing and monitoring signal, specifically including environmental temperature and humidity sensing and monitoring, soil temperature and humidity sensing and monitoring, illumination intensity sensing and monitoring, and the like.
Specifically, fig. 10 shows a block diagram of a basic sensing and monitoring unit 103 in the system according to the embodiment of the present invention.
In a preferred embodiment provided by the present invention, the basic sensing and monitoring unit 103 specifically includes:
and a period planning module 1031, configured to plan a basic induction period according to the phase analysis result.
And a signal generating module 1032 configured to periodically generate a sensing monitoring signal according to the basic sensing period.
And the induction monitoring module 1033 is used for carrying out induction monitoring on the environmental data of the agricultural greenhouse according to the induction monitoring signal.
Further, agricultural greenhouse intelligent monitoring system based on thing networking still includes:
and the activity analysis and identification unit 104 is used for performing real-time activity analysis on the monitoring shooting video, judging whether agricultural activities exist or not, and identifying the agricultural activity types when the agricultural activities exist.
In the embodiment of the present invention, the activity analysis and recognition unit 104 performs real-time activity analysis on the monitoring captured video to generate an activity analysis result, and determines whether agricultural activity exists in the agricultural greenhouse in real time according to the activity analysis result, and when agricultural activity exists, intercepts a corresponding activity captured video, and performs activity identification and analysis on the activity captured video to determine the type of agricultural activity performed in the agricultural greenhouse, specifically, the type of agricultural activity includes: watering, fertilizing, turning soil and the like.
And the adjusting induction monitoring unit 105 is used for adjusting the basic induction cycle according to the agricultural activity type, generating an adjusting induction cycle, determining an adjusting time period, and performing induction monitoring on the environmental data of the agricultural greenhouse according to the adjusting induction cycle in the adjusting time period.
In the embodiment of the present invention, the adjustment sensing monitoring unit 105 analyzes the period adjustment of the sensing monitoring according to the agricultural activity type to generate adjustment guidance information, and then adjusts the basic sensing period according to the adjustment guidance information to generate an adjustment sensing period, and determines an adjustment time period, so that after the agricultural activity, in the adjustment time period, the sensing monitoring signal is periodically generated according to the adjustment sensing period, and then the environmental data of the agricultural greenhouse is periodically sensed and monitored according to the corresponding sensing monitoring signal.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of steps in various embodiments may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed alternately or alternatingly with other steps or at least a portion of sub-steps or stages of other steps.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by a computer program, which may be stored in a non-volatile computer readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is specific and detailed, but not to be understood as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. An intelligent monitoring method for an agricultural greenhouse based on the Internet of things is characterized by comprising the following steps:
carrying out real-time monitoring shooting in an agricultural greenhouse to generate a monitoring shooting video, carrying out agricultural product analysis, and periodically extracting a plurality of agricultural target images;
acquiring stage image information corresponding to agricultural products, and performing stage analysis on a plurality of agricultural target images to generate stage analysis results;
planning a basic induction cycle according to the stage analysis result, and carrying out induction monitoring on the environmental data of the agricultural greenhouse according to the basic induction cycle;
performing real-time activity analysis on the monitoring shooting video, judging whether agricultural activities exist or not, and identifying the types of the agricultural activities when the agricultural activities exist;
and adjusting the basic induction cycle according to the agricultural activity type to generate an adjustment induction cycle, determining an adjustment time period, and performing induction monitoring on the environmental data of the agricultural greenhouse according to the adjustment induction cycle in the adjustment time period.
2. The intelligent monitoring method for the agricultural greenhouse based on the internet of things as claimed in claim 1, wherein the steps of performing real-time monitoring shooting in the agricultural greenhouse, generating a monitoring shooting video, performing agricultural product analysis, and periodically extracting a plurality of agricultural target images specifically comprise:
carrying out real-time monitoring shooting in an agricultural greenhouse to generate a monitoring shooting video;
performing frame-by-frame processing on the monitoring shooting video to obtain a plurality of monitoring shooting images;
randomly selecting a plurality of target shot images from the plurality of monitoring shot images;
and carrying out agricultural product analysis on the plurality of target shooting images, and periodically extracting a plurality of agricultural target images.
3. The intelligent monitoring method for the agricultural greenhouse based on the internet of things as claimed in claim 1, wherein the step of obtaining the phase image information corresponding to the agricultural product target and performing phase analysis on a plurality of agricultural target images, and the step of generating the phase analysis result specifically comprises the following steps:
performing target identification according to the plurality of agricultural target images to obtain agricultural target information;
acquiring corresponding stage image information according to the agricultural target information;
and performing stage analysis and identification on the plurality of agricultural target images according to the stage image information to generate a stage analysis result.
4. The intelligent monitoring method for the agricultural greenhouse based on the internet of things as claimed in claim 1, wherein a basic sensing period is planned according to the stage analysis result, and the sensing monitoring of the environmental data of the agricultural greenhouse according to the basic sensing period specifically comprises the following steps:
planning a basic induction cycle according to the stage analysis result;
generating induction monitoring signals periodically according to the basic induction period;
and carrying out induction monitoring on the environmental data of the agricultural greenhouse according to the induction monitoring signal.
5. The intelligent monitoring method for the agricultural greenhouse based on the internet of things as claimed in claim 1, wherein the real-time activity analysis of the monitoring shooting video to judge whether agricultural activities exist and the identification of the agricultural activity types when the agricultural activities exist specifically comprises the following steps:
performing real-time activity analysis on the monitoring shooting video to generate an activity analysis result;
judging whether agricultural activities exist or not according to the activity analysis result;
when agricultural activities exist, intercepting corresponding activity shooting videos;
and performing activity recognition analysis according to the activity shooting video to determine the type of the agricultural activity.
6. The intelligent monitoring method for the agricultural greenhouse based on the internet of things as claimed in claim 4, wherein the adjusting the basic sensing period according to the type of the agricultural activity to generate an adjusting sensing period and determine an adjusting time period, and the sensing and monitoring of the environmental data of the agricultural greenhouse according to the adjusting sensing period in the adjusting time period specifically comprises the following steps:
performing periodic adjustment analysis according to the agricultural activity type to generate adjustment guide information;
adjusting the basic induction period according to the adjustment guide information to generate an adjustment induction period and determine an adjustment time period;
periodically generating an induction monitoring signal according to the adjustment induction period in the adjustment time period;
and carrying out induction monitoring on the environmental data of the agricultural greenhouse according to the induction monitoring signal.
7. The utility model provides an agricultural greenhouse intelligent monitoring system based on thing networking, a serial communication port, the system shoots processing unit, target stage analysis unit, basic response monitoring unit, activity analysis recognition unit and adjusts the response monitoring unit including the control, wherein:
the monitoring shooting processing unit is used for carrying out real-time monitoring shooting in the agricultural greenhouse, generating a monitoring shooting video, carrying out agricultural product analysis and periodically extracting a plurality of agricultural target images;
the target stage analysis unit is used for acquiring stage image information corresponding to agricultural products, performing stage analysis on a plurality of agricultural target images and generating stage analysis results;
the basic induction monitoring unit is used for planning a basic induction period according to the stage analysis result and carrying out induction monitoring on the environmental data of the agricultural greenhouse according to the basic induction period;
the activity analysis and identification unit is used for carrying out real-time activity analysis on the monitoring shooting video, judging whether agricultural activities exist or not, and identifying the types of the agricultural activities when the agricultural activities exist;
and the adjusting induction monitoring unit is used for adjusting the basic induction period according to the agricultural activity type, generating an adjusting induction period, determining an adjusting time period, and performing induction monitoring on the environmental data of the agricultural greenhouse according to the adjusting induction period in the adjusting time period.
8. The intelligent monitoring system for the agricultural greenhouse based on the internet of things as claimed in claim 7, wherein the monitoring shooting processing unit specifically comprises:
the monitoring shooting module is used for carrying out real-time monitoring shooting in the agricultural greenhouse to generate a monitoring shooting video;
the frame-by-frame processing module is used for carrying out frame-by-frame processing on the monitoring shooting video to obtain a plurality of monitoring shooting images;
the random selection module is used for randomly selecting a plurality of target shooting images from a plurality of monitoring shooting images;
and the image extraction module is used for carrying out agricultural product analysis on the plurality of target shooting images and periodically extracting a plurality of agricultural target images.
9. The intelligent monitoring system for the agricultural greenhouse based on the internet of things as claimed in claim 7, wherein the target stage analysis unit specifically comprises:
the target identification module is used for carrying out target identification according to the agricultural target images to obtain agricultural target information;
the information acquisition module is used for acquiring corresponding stage image information according to the agricultural target information;
and the stage analysis module is used for performing stage analysis and identification on the plurality of agricultural target images according to the stage image information to generate a stage analysis result.
10. The intelligent monitoring system for the agricultural greenhouse based on the internet of things as claimed in claim 7, wherein the basic sensing and monitoring unit specifically comprises:
the period planning module is used for planning a basic induction period according to the stage analysis result;
the signal generation module is used for periodically generating induction monitoring signals according to the basic induction period;
and the sensing monitoring module is used for sensing and monitoring the environmental data of the agricultural greenhouse according to the sensing monitoring signal.
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