TWI663517B - Artificial intelligence integration system and analysis method - Google Patents

Abstract

The invention relates to an artificial intelligence integration system and an analysis method thereof. The main structure includes at least a sampling device, an analysis module, at least an environmental detection device, an operation interface, a first axial input unit, and a second shaft. An analysis platform that integrates modules with input units and charts, and an optimization module. In this way, sample data is collected for at least one target, and the sample data is analyzed to generate complex quantitative parameters according to different quantitative indicators, and the surrounding environment of the target is detected to obtain multiple environments according to different environmental conditions. Parameters, and then input the quantified indicators and environmental conditions as X and Y axes, and record the quantized parameters and environmental parameters on the statistical chart with indicators to quickly indicate the optimization conditions by the superimposed effect of the indicators.

Description

Artificial intelligence integration system and analysis method

The invention provides an artificial intelligence integration system and an analysis method thereof, particularly an artificial intelligence integration system that can automatically comprehensively compare quantitative indicators and environmental conditions, and integrate optimized production conditions to facilitate the monitoring and management of industrial production processes. And its analysis methods.

According to Taiwan's subtropical climate, it is not easy to cultivate plants due to the changing climate. Therefore, the development of an integrated system suitable for the climate pattern of Taiwan is one of the priorities for the development of fine agriculture. Affected by pests or natural disasters, isolating the damage from diseases and insects and reducing the loss of natural disasters can allow people to eat vegetables and fruits without pesticides or enjoy beautiful flowers with peace of mind. Therefore, automated management is also a future trend.

However, for some crops with high economic value, people must always pay attention to the adjustment of various environmental conditions in the growing environment, such as temperature, humidity, or illumination. At present, the current plant control methods are manually operated by users. The operation is performed and the related environmental control equipment is operated according to the farmers' past planting experience. However, due to limited manpower and the environment changes from time to time, especially the planting itself is not a simple matter. For a variety of plant varieties For those who lack planting experience, they will encounter many problems: they do n’t know about the growth environment of a certain plant, they do n’t know how to solve the problems encountered in the current plant growth status, they do n’t have a reminder about the poor growth management of plants, and Growth of cultivated plants lacks records.

However, the above plant control methods have the following problems and shortcomings that need to be improved:

1. Most of them are managed manually, the cost of personnel is high, the species are complex, and the environmental conditions are different. It is difficult to provide more accurate and stable management.

2. Existing scientific and technological management methods, which only provide automatic records, cannot effectively integrate or help farmers make decisions, or provide optimization suggestions and specific environmental management.

Therefore, how to solve the above-mentioned conventional problems and shortcomings is the direction in which the inventors of the present invention and related manufacturers engaged in this industry are eager to study and improve.

Therefore, the inventor of the present invention, in view of the above-mentioned shortcomings, collected relevant information, evaluated and considered from various parties, and based on years of experience accumulated in this industry, through continuous trial and error, he began to design such an automatic comprehensive comparison Quantitative indicators and environmental conditions, and the inventor of an artificial intelligence integration system and its analysis methods that optimize the production conditions to facilitate the monitoring and management of industrial production processes.

The main purpose of the present invention is to automatically integrate optimized production conditions according to different quantitative indicators and environmental conditions to improve the effectiveness of production process control.

Another main objective of the present invention is to: according to the quality requirements of each target object, freely set quantitative indicators, and freely change the detected environmental conditions according to the different growth environment requirements of each target object, and provide the most suitable target object. The integrated function of optimization to achieve the purpose of automatic analysis and assist farmers' decision-making.

To achieve the above object, the main structure of the present invention includes: at least one sampling device for collecting sample data of a target object, the sampling device information is connected with an analysis module, and at least one environmental detection device is provided on one side of the target object And has an analysis platform with information linking the sampling device and the environmental detection device, the analysis platform includes an operation interface, a first axial input unit defined on the operation interface, and an operation interface A second axial input unit, and a chart integration module that connects the first axial input unit and the second axial input unit with information, and defines an optimization on the analysis platform for indicating optimization conditions Module.

With the above structure, the sampling device first collects sample data for at least one target object, and then the analysis module analyzes the sample data to generate complex quantitative parameters according to different quantitative indicators, and at the same time uses the environmental detection device for the target object. The surrounding environment is detected to obtain a plurality of environmental parameters according to different environmental conditions, and then the user opens the operation interface to input a quantitative index into the analysis platform through a first axial input unit, and the environmental conditions through a second axis Enter the analysis platform into the input unit, then read the quantitative parameters and environmental parameters through the chart integration module to record the complex indicators on a statistical chart, and finally use the optimization module to selectively superimpose the indicators on the chart. Statistics chart to indicate optimization conditions. In this way, the user's manual operation is reduced, and the optimization conditions that meet the needs are integrated in a statistical manner, which effectively helps the user to manage.

With the above technology, it can break through the problems of higher personnel costs, unstable control efficiency, ineffective integration of parameters, and inability to provide optimization suggestions, specific management methods, or help farmers make decisions in the conventional plant control method. To achieve the practical and progressive nature of the above advantages.

1‧‧‧ sampling device

11‧‧‧ sample data

2‧‧‧analysis module

21, 21a, 21b ‧ ‧ Quantitative indicators

211, 211a‧‧‧Quantitative parameters

3‧‧‧Environmental Detection Device

31, 31a‧‧‧Environmental conditions

311, 311a‧‧‧Environmental parameters

4, 4a, 4c ‧‧‧ analysis platform

41, 41a‧‧‧ operation interface

42, 42a‧‧‧First axial input unit

43, 43a‧‧‧Second axial input unit

44a‧‧‧Third axial input unit

45‧‧‧Chart Integration Module

451, 451b‧‧‧ statistics chart

452a‧‧‧Three-dimensional statistical chart

5, 51, 52, 53‧‧‧ indicator

6, 6b‧‧‧optimized module

61b‧‧‧weighting unit

611b‧‧‧weight index

7c‧‧‧Mobile electronic device

71c‧‧‧Real-time monitoring software

72c‧‧‧Comparison database

8‧‧‧ target

A‧‧‧Stem length

B‧‧‧ blade width

C‧‧‧ blade width

D‧‧‧Blade thickness

The first figure is a block diagram showing the structure of a preferred embodiment of the present invention.

The second figure is a block flow diagram of a preferred embodiment of the present invention.

The third diagram is a schematic diagram of sampling in the preferred embodiment of the present invention.

The fourth diagram is an analysis diagram of a preferred embodiment of the present invention.

The fifth figure is a schematic diagram of detection in the preferred embodiment of the present invention.

The sixth figure is a use state diagram of the analysis platform of the preferred embodiment of the present invention.

The seventh diagram is a schematic diagram of a statistical chart of a preferred embodiment of the present invention.

The eighth figure is a schematic diagram of the optimization of the preferred embodiment of the present invention.

The ninth figure is a structural block diagram of yet another preferred embodiment of the present invention.

The tenth figure is a schematic diagram of a three-dimensional diagram according to still another preferred embodiment of the present invention.

The eleventh figure is a structural block diagram of another preferred embodiment of the present invention.

The twelfth figure is a weight diagram of another preferred embodiment of the present invention.

The thirteenth figure is a schematic diagram of remote monitoring according to another preferred embodiment of the present invention.

In order to achieve the above-mentioned object and effect, the technical means and structure adopted by the present invention are described in detail below with reference to the preferred embodiments of the present invention.

Please refer to the first and second figures, which are structural block diagrams and block flowcharts of the preferred embodiment of the present invention. It can be clearly seen from the figure that the present invention includes: at least one sampling device 1 A target object 8 collects sample data 11; an information is connected to the analysis module 2 of the sampling device 1 for analyzing the sample data 11 to generate complex quantitative parameters 211 according to different quantitative indicators 21, the analysis module 2 is Is an image analysis device, and the quantization index 21 is set by the image analysis device or can be defined by the user's experience; at least one environmental detection device 3 located on the side of the target 8 is the target 8 The surrounding environment is detected to obtain a plurality of environmental parameters 311 according to different environmental conditions 31; an information linking the sampling device 1 and the analysis platform 4 of the environmental detection device 3, the analysis platform 4 includes an operation interface 41, a A first axial input unit 42 defined on the operation interface 41 for inputting the quantitative indicators 21, a second axial input unit 43 defined on the operation interface 41 for inputting the environmental conditions 31, and a Coupling the first information input unit 42 and the axial The chart integration module 45 of the second axial input unit 43 is for generating a statistical chart 451, and the analysis platform 4 records the quantitative parameters 211 and the environmental parameters 311 in the statistical chart with a complex indicator 5 451; and an optimization module 6 defined on the analysis platform 4, the indicator symbols 5 are superimposed on the statistical chart 451 to indicate the optimization conditions.

In addition, the artificial intelligence integrated analysis method of the present invention includes the steps of: (a) collection of sample data; (b) selection of quantitative indicators and analysis of quantified parameters; (c) selection of environmental conditions and detection of environmental parameters (D) in the operation interface, set the quantitative index to the first axis; (e) in the operation interface, set the environmental conditions to the second axis; (f) record the indicator on the statistical chart; and ( g) the generation of optimized conditions.

With the above explanation, we can understand the structure of this technology, and according to the corresponding cooperation of this structure, we can automatically compare and compare quantitative indicators 21 and environmental conditions 31 to integrate optimized production conditions, which is beneficial to industrial production. The advantages of process monitoring and management, and a detailed explanation will be described below.

Please also refer to the first to eighth diagrams, which are structural block diagrams to optimization diagrams of the preferred embodiment of the present invention. When the above components are assembled, it can be clearly seen from the diagram that The sampling device 1 is implemented by a network camera, and the analysis module 2 is implemented by an image editing management program. As for the environmental detection device 3, various sensors are used, such as temperature sensors and air humidity sensors. The target object 8 is set as a flower in this embodiment, so the quantification index 21 can be the number of blossoms, the number of leaves, the color of the petals, the size of the petals, the size of the buds, the length of the pedicels, and the length of the stalks A (buds or flowers and At least one of pedicel length between soil surfaces), pedicel number, pedicel diameter, leaf width B, leaf width C, penultimate leaf thickness D, or chlorophyll content, and environmental condition 31 may be air temperature (° C ), Air humidity (%), light intensity (lumens lm), soil moisture (VWC% (Volumetric Water Content)), soil pH (PH), fertilizer (EC (soil electrical conductivity)) Or sunshine time (h r) at least one of them.

In actual use, the sampling device 1 is first used to collect sample data 11 of a target object 8, such as the appearance of the image or the sampling of components (such as step a and the third picture), and then use the obtained sample data 11 to analyze Module 2 performs analysis and generates a plurality of quantization parameters 2 according to different quantization indicators 21 11 (as in step b, the fourth and seventh figures), if the quantified index 21 is the number of flowers, the analysis module 2 uses the technology of the image editing management program to capture the image, optimize the image, and segment the image. Actions such as identification of target and target 8 automatically analyze the number of flowers and generate a quantified parameter 211 (6 to 10). As for the color of the petals, it is an example that cannot be quantified normally. Therefore, the user will determine based on personal experience. The color of the petals is close to the levels of white, pale pink, pink, purple pink, and pink, and the quantization parameter 211 (1 to 5) is customized.

At the same time, use the environmental detection device 3 to detect the surrounding environment of the target 8 (such as the inside of the soil and the surrounding air) to obtain a plurality of environmental parameters 311 according to different environmental conditions 31 (such as step c and the fifth figure), and then , The user opens the analysis platform 4 and operates an operation interface 41 to input the quantitative indicators 21 through the first axial input unit 42 to the analysis platform 4 (as shown in step d and the sixth figure), and The environmental conditions 31 are input to the analysis platform 4 through the second axial input unit 43 (as shown in step e and the sixth figure). At this time, the graph integration module 45 can be used to read the quantitative parameters 211 and the environmental parameters. 311, and record it on a statistical chart 451 with a complex indicator 5 (such as step f and the seventh chart). In this embodiment, the first axis (X axis) of the statistical chart 451 is the number of flowers and the color of the petals. The second axis (Y-axis) of the statistical chart 451 is air humidity, fertilizer, and soil moisture, and the indicator 5 distinguishes various quantitative indicators 21 with different colors or shapes.

Finally, the optimization module 6 is used to superimpose the indicator symbols 5 in the different quantization indicators 21 on the statistical chart 451, and when each indicator symbol 5 overlaps on the statistical chart 451, it is automatically changed to a different color or symbol. Represents superimposed appearance. Specifically, the indicator 51 in the field of the quantified indicator 21 representing the number of flowers is a triangle, and the indicator 52 in the field of the quantitative indicator 21 of the petal color is exemplified as a square. The optimization module 6 will calculate the statistical chart. In 451, the indicator 51 representing the number of flowers is copied into the field representing the color of the petals. At this time, because other indicators 52 already exist in the field representing the color of the petals, when the two indicators 5 overlap, The optimization module 6 will change the indicator 5 in the overlapping part to the indicator 53 (such as a pentagon) in a superimposed state. In this way, the user can observe the statistical chart 451 under which environmental conditions 31 have the most superimposed indicators 5, which means that these environmental conditions 31 can simultaneously meet the requirements of all quantitative indicators 21, and You can simply see the optimized conditions (such as the highest market value or the appreciation standards of the designated country) to automatically integrate the optimized production conditions, thereby assisting farmers in making decisions and improving the effectiveness of production process control.

Please also refer to the ninth and tenth figures at the same time, which is the conclusion of another preferred embodiment of the present invention. A block diagram and a three-dimensional diagram are clearly shown in the figure. This embodiment is similar to the above embodiment. Only the analysis platform 4a further includes a third axial input unit 44a defined on the operation interface 41a. For inputting time parameters, the statistical graph is converted into a three-dimensional statistical graph 452a. In this way, the time parameters are combined with the first axial input unit 42a and the second axial input unit 43a, and the quantized parameters 211a and environmental parameters 311a obtained at different points in time are recorded on the three-dimensional statistical chart 452a, respectively. It can be simply judged that in different growth periods (such as spring, summer, autumn, winter, or daily changes), in order to meet the needs of various quantitative indicators 21a, it is necessary to control what environmental parameters 311a the environmental conditions 31a are in, so that users can be more accurate and stable. Control optimization conditions.

Please also refer to FIG. 11 and FIG. 12 at the same time, which are structural block diagrams and weight diagrams of another preferred embodiment of the present invention. It can be clearly seen from the figure that this embodiment and the above embodiment For the sake of similarity, only the optimization module 6b includes a weighting unit 61b to assign a weighting index 611b to each of the quantitative indexes 21b, and sequentially arrange each of the quantitative indexes 21b on the statistical chart 451b according to the size of the weighting index 611b. on. Specifically, when there are many types of quantization indicators 21b, as long as the weighting unit 61b is used to set the weighting index 611b, for example, the weighting index 611b of the number of flowers is set to 40%, the weighting index of the petal color is 611b, and the weighting of the petal size is set. The index 611b is 30%, and the weight index 611b of the number of leaves is 10%. The weighting unit 61b will arrange the quantitative indicators 21b according to the weight index 611b, and from the origin of the statistical chart 451b to the number of flowers, Petal size, petal color, and number of leaves for easy viewing.

Please also refer to FIG. 13 at the same time, which is a schematic diagram of remote monitoring according to another preferred embodiment of the present invention. As can be clearly seen from the figure, this embodiment is similar to the above embodiment, but also includes a The real-time monitoring software 71c, which is set in a mobile electronic device 7c, and the information is linked to the analysis platform 4c, and a comparison database 72c, which is linked to the real-time monitoring software 71c, is to compare the environmental parameters with the comparison data in real time. Library 72c. The real-time monitoring software 71c is a mobile application (APP), and the comparison database 72c can be stored in the mobile electronic device 7c or stored in a cloud server. As a result, the user only needs to open the real-time monitoring software 71c in the mobile electronic device 7c, and then can connect to the analysis platform 4c through the network to obtain various environmental parameters. Then, the real-time monitoring software 71c can automatically refer to the comparison database 72c. When the real-time data of the environmental parameters and the comparison database 72c are different or exceed the allowable range, the user will be notified through the real-time monitoring software 71c (for example, the icon frame corresponding to the environmental parameters is illuminated or changed color for warning) ) Or even borrow With the technology of the Internet of Things, the electronic equipment (such as air conditioners, sprinklers, humidifiers, etc.) where the target is located is remotely controlled to achieve the purpose of real-time monitoring.

However, the above description is only the preferred embodiment of the present invention, and it does not limit the patent scope of the present invention. Therefore, all simple modifications and equivalent structural changes made by using the description and drawings of the present invention should be the same. It is included in the patent scope of the present invention and is incorporated by Chen Ming.

In summary, when the artificial intelligence integration system and its analysis method of the present invention are used, in order to truly achieve its efficacy and purpose, the present invention is an invention with excellent practicability. In order to meet the application requirements of the invention patent, 爰The application is submitted in accordance with the law, and I hope the review committee will grant the present invention as soon as possible to protect the inventor's hard invention. If there is any suspicion by the review committee of the Bureau, please follow the instructions of the letter, and the inventor will cooperate with all efforts and be honest.

Claims (8)

An artificial intelligence integrated system mainly includes: at least one sampling device that collects sample data of at least one target; an information linking analysis module of the sampling device for analyzing the sample data to analyze different sample data Generate complex quantitative parameters, the analysis module is an image analysis device, and the quantization index is set by the image analysis device; at least one environmental detection device located on the side of the target object is the surrounding environment of the target object Perform detection to obtain a plurality of environmental parameters according to different environmental conditions; an information linking the sampling device and an analysis platform of the environmental detection device, the analysis platform includes an operation interface, and an input interface defined on the operation interface A first axial input unit for quantifying an index, a second axial input unit defined on the operation interface for inputting the environmental conditions, and an information linking the first axial input unit and the second axial input unit The chart integration module is used to generate a statistical chart, and the analysis platform is to quantify the parameters and the environmental parameters Complex indicator recorded on the charts; and an optimization module defined on the analysis of the platform, the more indicator line superimposed on the charts, indicating the best conditions. According to the artificial intelligence integration system described in item 1 of the scope of patent application, the analysis platform further includes a third axial input unit defined on the operation interface for inputting time parameters to convert the statistical chart into a three-dimensional summary graph. The artificial intelligence integration system described in item 1 of the scope of patent application, wherein the optimization module includes a weight unit, which assigns a weight index to each of the quantitative indexes, and sequentially quantifies each of the quantitative indexes according to the size of the weight index. Arranged on the statistical chart. The artificial intelligence integration system described in item 1 of the scope of patent application, which further includes a real-time monitoring software installed in a mobile electronic device and information linked to the analysis platform, and a comparison database of information linked to the real-time monitoring software , The real-time comparison of these environmental parameters with the comparison database. An analysis method for an artificial intelligence integrated system, the steps include: (a) using at least one sampling device to collect sample data for at least one target object; (b) analyzing the sample data using an analysis module to quantify according to different The indicator generates complex quantitative parameters, wherein the analysis module is an image analysis device, and the quantization indicator is set by the image analysis device; (c) using at least one environmental detection device to detect the surrounding environment of the target, To obtain a plurality of environmental parameters according to different environmental conditions; (d) operating an operating interface of an analysis platform to input the quantitative indicators into the analyzing platform through a first axial input unit; (e) operating the operating interface to The environmental conditions are input to the analysis platform through a second axial input unit; (f) the quantitative parameters and the environmental parameters are read through the graphic integration module of the analysis platform, and are recorded with a complex indicator On a statistical chart; and (g) using an optimization module to selectively superimpose the indicator symbols on the statistical chart to indicate optimization conditions. The analysis method of the artificial intelligence integration system described in item 5 of the scope of patent application, further including step (e1) using a third axial input unit to combine time parameters with the first axial input unit and the second The axis is inputted to generate a three-dimensional statistical graph. According to the analysis method of the artificial intelligence integration system described in item 5 of the scope of patent application, it further includes step (g1) using a weight unit to assign a weight index to each of the quantified indicators, and sequentially according to the size of the weight index, Quantitative indicators are arranged on the statistical chart. The analysis method of the artificial intelligence integration system described in item 5 of the scope of patent application, further including step (h) using the real-time monitoring software information in the mobile electronic device to connect to the analysis platform, and passing the environmental parameters through the real-time monitoring Software information is linked to a comparison database for real-time comparison.