Information processing system, information processing method, and program

Abstract

To accurately estimate water content of a target object in consideration of the situation that it is often affected by a peripheral environment when estimating the water content of a surface of iron ore pile, making it difficult to manage appropriate values.SOLUTION: An information processing system 1000 includes: acquiring optical characteristics of a substance 130; acquiring information on inclination of a surface of the substance; and estimating water content of the substance in accordance with the optical characteristics and inclination information.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an information processing system, an information processing method, and a program. [Background technology]

[0002] For materials such as iron ore and coal used as raw materials for steelmaking or fuel for power generation, it is necessary to maintain the moisture content of the material within an appropriate range. If the material is too dry, dust will be generated, while if the moisture content is too high, clogging may occur during transportation or a large amount of heat may be required for drying, resulting in reduced energy efficiency.

[0003] Therefore, it is necessary to understand the amount of water contained in the material in order to maintain the moisture content within an appropriate range by sprinkling water when it is dry, or spraying chemicals such as water-blocking agents when the moisture content is too high.

[0004] In order to grasp the moisture content in the material and perform water sprinkling to prevent dust, Patent Document 1 discloses a method for measuring the moisture content on the surface of an iron ore pile using a near-infrared moisture content meter. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2008-050076 A Summary of the Invention [Problem to be solved by the invention]

[0006] However, the inventors have found through their investigations that when estimating the moisture content, etc., of the surface of the pile as described above, it is often affected by the surrounding environment, and it is sometimes difficult to properly manage the numerical values.

[0007] In view of the above circumstances, an object of the present invention is to properly estimate the moisture content, etc., of an object. [Means for solving the problem]

[0008] According to one aspect of the present invention, there is provided an information processing system, the information processing system comprising: acquiring optical characteristics of an object; acquiring information on a surface slope of the object; and estimating a water content of the object based on the optical characteristics and the information on the slope.

[0009] The following additional notes may also be adopted. (Appendix 1) An information processing system, Acquire the optical properties of the object, Obtaining information about the inclination of a surface of the object; estimating a water content of the object based on the optical property and the tilt information; Information processing system. (Appendix 2) In the information processing system according to claim 1, Inputting the optical characteristics and the tilt information into a trained model; The trained model is a trained model trained using optical properties of an object and information on the inclination of the surface of the object as input data and water content of the object as output data, Obtaining the water content output from the trained model as an estimation result; Information processing system. (Appendix 3) An information processing system, Acquire the optical properties of the object, Obtaining information about the inclination of a surface of the object; Estimating the presence or absence of a drug or the amount of the drug contained in the object based on the optical characteristics and the tilt information. Information processing system. (Appendix 4) In the information processing system according to claim 3, Inputting the optical characteristics and the tilt information into a trained model; The trained model is a trained model trained using the optical characteristics of an object and information on the inclination of the surface of the object as input data, and the presence or absence or content of a drug in the object as output data, The presence or absence or amount of the drug output from the trained model is obtained as a result of estimation. Information processing system. (Appendix 5) In the information processing system according to any one of Supplementary Note 1 to Supplementary Note 4, The inclination information is either or both of the slope direction and the slope angle of the object. Information processing system. (Appendix 6) In the information processing system according to claim 5, acquiring the tilt information from a sensor; Information processing system. (Appendix 7) An information processing system, Acquire the optical properties of the object, acquiring information about a position of a light source relative to the object; estimating the water content of the object based on the optical characteristics and the information on the position of the light source; Information processing system. (Appendix 8) In the information processing system according to claim 7, Inputting the optical characteristics and the information on the position of the light source into a trained model; The trained model is a trained model trained using optical characteristics of an object and information on the position of a light source relative to the object as input data and water content of the object as output data, Obtaining the water content output from the trained model as an estimation result; Information processing system. (Appendix 9) An information processing system, Acquire the optical properties of the object, acquiring information about a position of a light source relative to the object; Estimating the presence or absence or amount of a drug contained in the object based on the optical characteristics and information on the position of the light source. Information processing system. (Appendix 10) In the information processing system according to claim 9, Inputting the optical characteristics and the information on the position of the light source into a trained model; The trained model is a trained model trained using the optical characteristics of an object and information on the position of a light source relative to the object as input data, and the presence or absence of a drug in the object or the amount of the drug as output data, Obtaining the presence or absence or amount of a drug in the object output from the trained model as an estimation result; (Appendix 11) In the information processing system according to any one of Supplementary Note 7 to Supplementary Note 10, The information on the position of the light source is either or both of information on the altitude of the light source relative to the object and information on the orientation of the light source relative to the object. Information processing system. (Appendix 12) In the information processing system according to any one of Supplementary Note 1 to Supplementary Note 11, Output the estimation results, Information processing system. (Appendix 13) An information processing method executed by an information processing system, comprising: Acquire the optical properties of the object, Obtaining information about the inclination of a surface of the object; estimating a water content of the object based on the optical property and the tilt information; Information processing methods. (Appendix 14) An information processing method executed by an information processing system, comprising: Acquire the optical properties of the object, Obtaining information about the inclination of a surface of the object; Estimating the presence or absence of a drug or the amount of the drug contained in the object based on the optical characteristics and the tilt information. Information processing methods. (Appendix 15) An information processing method executed by an information processing system, comprising: Acquire the optical properties of the object, acquiring information about a position of a light source relative to the object; estimating the water content of the object based on the optical characteristics and the information on the position of the light source; Information processing methods. (Appendix 16) An information processing method executed by an information processing system, comprising: Acquire the optical properties of the object, acquiring information about a position of a light source relative to the object; Estimating the presence or absence or amount of a drug contained in the object based on the optical characteristics and information on the position of the light source. Information processing methods. (Appendix 17) A program, Computer, A program for causing the information processing system according to any one of claims 1 to 12 to function as such.

[0010] According to the above aspect, the water content, etc. of the object can be appropriately estimated. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a diagram illustrating an example of a system configuration of an information processing system 1000. As shown in FIG. [Diagram 2] FIG. 2 is a diagram illustrating an example of a hardware configuration of a PC. [Diagram 3] FIG. 3 is an activity diagram showing an example of information processing in a PC. [Figure 4] FIG. 4 is an activity diagram showing an example of information processing in the PC of the first modification. [Diagram 5] FIG. 5 is a diagram illustrating an example of a system configuration of an information processing system according to the second modification. [Figure 6] FIG. 6 is an activity diagram showing an example of information processing in a PC according to the third modification. [Figure 7] FIG. 7 is an activity diagram showing an example of information processing in a PC according to the fourth modification. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, an embodiment of the present invention will be described. Note that various characteristic features shown in the following embodiment 1 (including the modified examples described below, which also apply hereinafter) can be combined with each other.

[0013] Incidentally, the program for realizing the software appearing in embodiment 1 may be provided as a non-transitory computer-readable recording medium, or may be provided so as to be downloadable from an external server, or may be provided so that the program is started on an external computer and its functions are realized on a client terminal (so-called cloud computing).

[0014] Furthermore, in the first embodiment, the term "unit" may include, for example, a combination of hardware resources implemented by a circuit in the broad sense and software information processing that can be specifically realized by these hardware resources. Furthermore, in the first embodiment, various information is handled, and this information is represented, for example, by physical values ​​of signal values ​​representing voltage and current, high and low signal values ​​as a binary bit collection consisting of 0 or 1, or quantum superposition (so-called quantum bits), and communication and calculation can be performed on the circuit in the broad sense.

[0015] In addition, a circuit in the broad sense is a circuit realized by at least appropriately combining a circuit, circuitry, a processor, a memory, etc. In other words, it includes an application specific integrated circuit (ASIC), a programmable logic device (e.g., a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)), etc.

[0016] 1. System Configuration Fig. 1 is a diagram showing an example of a system configuration of an information processing system 1000. As shown in Fig. 1, the information processing system 1000 includes, as a system configuration, a PC (Personal Computer) 100 and an aircraft 110. The PC 100 and the aircraft 110 are connected via a network 150 so as to be able to communicate with each other.

[0017] The PC 100 executes information processing described in the first embodiment. Details of the information processing in the PC 100 will be described using an activity diagram and the like described later. The aircraft 110 includes an imaging unit 120. The aircraft 110 flies above the substance 130 and images the substance 130 with the imaging unit 120. The substance 130 is an object for which the moisture content, etc., is to be estimated. The substance 130 may be inorganic or organic. In the first embodiment, the substance 130 will be described as being a raw material for ironmaking or a fuel for power generation.

[0018] "Ironmaking raw materials" refers to materials used as raw materials and fuels for ironmaking in ironmaking facilities such as steelworks, and examples of such materials include coal, steel, dust, slag, coke, sintered ore, as well as auxiliary materials such as limestone and dolomite. "Power generation fuel" refers to materials used as fuels for power generation in power generation facilities such as power plants, and examples of such materials include coal and biomass fuels. In a more typical example, material 130 is coal or iron ore. In the specification, the "water content" may be an absolute mass amount, or may be a concept including the water content per unit mass of a substance, that is, the water content rate.

[0019] The flying object 110 photographs the substance 130 from the sky with the photographing unit 120. A more specific example of the photographing unit 120 is a hyperspectral camera or a multispectral camera. The multispectral camera is a camera that can observe wavelengths in the near-infrared band in addition to the visible light band. The hyperspectral camera is a camera that can obtain more detailed information because it has a much larger number of observable bands than the multispectral camera. The flying object 110 transmits the spectral information acquired by the photographing unit 120 to the PC 100 via the network 150. A more specific example of the flying object 110 is a drone. In the first embodiment, the flying object 110 transmits the spectral information acquired by the photographing unit 120 to the PC 100 via the network 150, but the spectral information may be stored in a storage medium or the like. The PC 100 into which the storage medium is inserted may read the spectral information of the substance 130 from the storage medium.

[0020] Here, the information processing system described in the claims may be composed of multiple devices or may be composed of one device. When the information processing system described in the claims is composed of one device, an example of the device is PC 100. When the information processing system described in the claims is composed of multiple devices, an example of the multiple devices is PC 100 and aircraft 110, or a cloud system composed of multiple servers that provide the functions of PC 100.

[0021] 2. Hardware Configuration (1) PC100 hardware configuration Fig. 2 is a diagram showing an example of a hardware configuration of PC 100. As shown in Fig. 2, PC 100 includes, as the hardware configuration, a control unit 210, a storage unit 220, an input unit 230, an output unit 240, and a communication unit 250.

[0022] The control unit 210 is a CPU (Central Processing Unit) or the like, and controls the entire PC 100 .

[0023] The storage unit 220 is any one of a hard disk drive (HDD), a read only memory (ROM), a random access memory (RAM), a solid state drive (SSD), etc., or any combination thereof, and stores a program and data used when the control unit 210 executes processing based on the program (for example, spectrum information transmitted from the aircraft 110, a trained model described later, training data when training the model, and data necessary for the training data, etc.). The storage unit 220 is an example of a storage medium. In the specification, the data used when the control unit 210 executes processing based on the program is described as being stored in the storage unit 220, but the data may be stored in a storage unit of another device that can communicate with the PC 100. In other words, the data may be stored in a storage unit of any device as long as the data can be referenced or used by the control unit 210. The control unit 210 executes processing based on the program stored in the storage unit 220, thereby realizing the functions of the PC 100 and the information processing of the activity diagrams of Figures 3 to 6 described later.

[0024] The input unit 230 is a keyboard, a mouse, or the like, and inputs operation information such as a user's selection operation and input operation. The output unit 240 is a display or the like, and displays information such as the results of processing by the control unit 310.

[0025] The communication unit 260 connects the PC 100 to the network 150 and controls communication with other devices.

[0026] (2) Hardware configuration of the flying vehicle 110 The flying object 110 includes a control unit, a memory unit, a communication unit, an image capture unit 120, etc. as hardware components. The control unit is a CPU, etc. The memory unit is a memory such as a RAM or a ROM. The control unit executes processing based on a program stored in the memory unit, thereby realizing the functions of the flying object 110, etc. The communication unit connects the flying object 110 to a network 150 and manages communication with other devices. An example of communication is wireless communication, etc. As described above, the image capture unit 120 is a hyperspectral camera or a multispectral camera, etc., and acquires spectral information of the substance 130, etc. For example, the image capture unit 120 irradiates the substance 130 from multiple angles and acquires the respective spectral information. The image capture unit 120 may also irradiate the substance 130 with polarized light and acquire the spectral information. In addition to these hardware components, there are other hardware components essential to the aircraft 110, such as a motor and propellers, but these will be omitted for the sake of simplicity.

[0027] 3. Information Processing 3 is an activity diagram showing an example of information processing in the PC 100. It is assumed that the spectral information of the substance 130 photographed by the photographing unit 120 of the flying object 110 is transmitted to the PC 100 and stored in the storage unit 220 together with information on the date and time of measurement, etc.

[0028] In activity A300, control unit 210 acquires spectral information of material 130 from storage unit 220, etc., and calculates optical properties of material 130 based on the acquired spectral information. Optical properties include absorptivity, reflectivity, transmittance, scattering rate, refractive index, polarization rate, etc. In the specification, the optical properties also include a value calculated as a function of the difference between two optical properties of the same material 130 for light of two different wavelengths.

[0029] For example, the optical characteristics for light with wavelengths inm and jnm are Oi , O j Then, the difference between the two optical properties is O j -O i The difference function is f(O j -O i ) is shown. i , O j may have the same optical properties or different optical properties. i , O j The "different optical properties" refers to the case where both are reflectances, e.g., O i is the reflectance, O j is the absorption rate.

[0030] The difference function is j There is no particular limitation as long as it is a function of -Oi. j -O i , C(O j -O i ), C / (O j -O i ), C Oj-Oi , e Oj-Oi , log(O j -O i ) (where C is an arbitrary constant) can be used. In addition, as a function of the difference, O i , O j For example, the following formulas (1) to (3) may be used.

[0031] (O j -O i ) / O j (1) (O j -O i ) / O i (2) (O j -O i ) / (O j +O i ) ···(3)

[0032] In one embodiment, the normalized difference spectral index (NDSI) can be used as the difference function. Specifically, the normalized difference spectral index is expressed as R i , R j Then, it is expressed by the following equation (4).

[0033] NDSI=(R j -R i ) / (R j +R i ) ···(4) Unless otherwise specified in the following specification, the optical property of the material 130 refers to the NDSI value calculated using equation (4).

[0034] The processing of activity A300 is an example of a processing for acquiring optical characteristics of the material 130 that is the target object.

[0035] In the activity A310, the control unit 210 obtains information on the inclination of the material 130 from the storage unit 220 or the like. Here, the control unit 210 acquires information on the inclination of the material 130 from a sensor installed on a platform or the like on which the material 130 is placed, and stores the information in the storage unit 220 or the like together with information on the date and time of measurement. An example of the sensor is a 3D gyro sensor or the like. However, this is not intended to limit the sensor. Any sensor may be used as long as it is installed directly on the material 130 to measure the inclination, or the inclination of a platform or the like on which the material 130 is placed can be measured to determine the inclination of the material 130. Alternatively, the control unit 210 may generate three-dimensional data from an image captured by the imaging unit 120, and measure the inclination of the generated three-dimensional data. The imaging unit 120 is also an example of a sensor. For example, the material 130 is photographed by another camera mounted on a drone or the like, and the photographed image is acquired. The control unit 210 may obtain the inclination of the material 130 from the three-dimensional data generated using the captured image. In such a configuration, other cameras are also an example of a sensor. The inclination information is either or both of the slope direction of the object (material 130 in the example of the first embodiment) and the slope angle of the object. The slope direction represents the direction of the slope in degrees clockwise, with north being 0 degrees, east being 90 degrees, south being 180 degrees, and west being 270 degrees. The slope angle represents the inclination of the slope, with horizontal being 0 degrees and vertical being 90 degrees. The inclination information may also include information obtained from either or both of the slope direction of the object and the slope angle of the object. The process of activity A310 is an example of a process of acquiring information on the inclination of the surface of the material 130, which is the object. In addition, if the control unit 210 can determine the slope orientation and slope angle of material 130, etc., of material 130 by image analysis (e.g., gloss) from multiple spectral information (multispectral image) of material 130 photographed by the photographing unit 120, the control unit 210 may determine the slope orientation and slope angle of material 130, etc., of material 130 in such a manner.

[0036] The order of processing activity A300 and activity A310 does not matter. Activity A300 may precede activity A310, or activity A300 may follow activity A310. Activity A300 and activity A310 may be executed simultaneously. However, control unit 210 acquires information on optical characteristics and tilt measured at the same date and time based on date and time information, etc.

[0037] In activity A320, control unit 210 acquires a trained model from memory unit 220 or the like, and inputs the optical properties of material 130 determined in activity A300 and the information on the surface inclination of material 130 determined in activity A310 to the acquired trained model. Here, the trained model is a trained model trained using the optical properties of material 130 and the information on the inclination of material 130 as input data and the water content of material 130 as output data. Control unit 210 acquires the water content output from the trained model as an estimated value. The processing of activity A320 is an example of processing for estimating the water content of material 130, which is an object, based on the optical properties and the inclination information. By carrying out such processing, the water content, etc., of the substance 130, which is the target object, can be appropriately estimated.

[0038] Although the control unit 210 uses a trained model when obtaining output data from input data, the control unit 210 may obtain output data from input data using a function indicating the relationship between the input data and the output data, a lookup table, or the like. The same applies to the following modified examples, etc.

[0039] In activity A330, control unit 210 outputs the acquired water content. Control unit 210 outputs the water content by generating a screen including the water content and displaying it on output unit 240, generating a file or the like including the water content and storing it in storage unit 220, or generating a file or the like including the water content and transmitting it to another device via communication unit 250. The processing of activity A330 is an example of processing to output the result of estimation.

[0040] According to the process of the first embodiment, it is possible to properly estimate the water content of the substance 130, which is the target object, and to output the result of the estimation to a screen or the like. Note that another example of the process of FIG. 3 performed by the control unit 210 is as follows. For example, when the mass of the substance 130 is arranged in a predetermined range or more, the control unit 210 may divide the range in which the substance 130 exists into certain ranges (areas). Then, the control unit 210 may execute the process shown in FIG. 3 for each range. For example, the control unit 210 may acquire the optical characteristics for each range and output the water content estimated for each range (area). The measurement range of the optical characteristics may be automatically determined by the control unit 210 based on the size of the mass of the substance 130 and instructed to the imaging unit 120, or may be determined based on a setting operation by the user via the input unit 230 or the like. When outputting the water content estimated for each range (area), the control unit 210 outputs the range and the estimated value of the range in association with each other. The control unit 210 may output the estimated value as a character or a numerical value, or may output the estimated value in a color corresponding to the estimated value. The control unit 210 may output these information in any combination. Such an output method also applies to the following FIGS. 4, 6, and 7.

[0041] (Variation 1) Modification 1 of embodiment 1 will be described. In modification 1, differences from embodiment 1 will be described. Modification 1 is a modification of a part of the processing of embodiment 1, and is included in embodiment 1 rather than being a different embodiment from embodiment 1. Fig. 4 is an activity diagram showing an example of information processing in the PC 100 of Modification 1. In Fig. 4, the same reference numerals are used for the same parts as those in the information processing in the activity diagram of Fig. 3.

[0042] In activity A420, the control unit 210 of the modified example 1 (hereinafter, simply referred to as the control unit 210) acquires the trained model of the modified example 1 (hereinafter, simply referred to as the trained model) from the storage unit 220 or the like, and inputs the optical properties of the substance 130 obtained in activity A300 and the information on the inclination of the surface of the substance 130 obtained in activity A310 to the acquired trained model. Here, the trained model is a trained model trained with the optical properties of the substance 130 and the information on the inclination of the substance 130 as input data, and the presence or absence of a drug in the substance 130 or the amount of the drug as output data. The control unit 210 acquires the presence or absence of a drug in the substance 130, which is the object, or the amount of the drug output from the trained model as an estimated value. The process of activity A420 is an example of a process for estimating the presence or absence of a drug in the substance 130, which is the object, or the amount of the drug. Here, the "drug" may be any known drug that can be combined with the substance 130. For example, if the material 130 (target object) is a raw material for iron making or a fuel for power generation, and the material 130 is piled up in a pile, the agent may be a dust suppressant.

[0043] The dust suppressant may be, but is not limited to, a wax emulsion solution, a resin emulsion solution, silicone oil, mineral oil, heavy oil, or the like. Wax emulsions are divided into natural wax and synthetic wax, depending on the raw material of the wax. Natural waxes include, but are not limited to, animal waxes (beeswax, spermaceti, etc.), vegetable waxes (carnauba wax, rice wax, candelilla wax, etc.), petroleum waxes (paraffin wax, microcrystalline wax, etc.), and mineral waxes (montan wax, ceresin wax, etc.). Synthetic waxes include, but are not limited to, polyethylene wax, modified natural wax, and hardened oils of oils and fats. The emulsion resin of the emulsion resin solution may be, but is not limited to, for example, an acrylic resin, an acrylic copolymer resin, a vinyl acetate resin, a synthetic rubber, a urethane resin, asphalt (emulsifier), an acrylic-styrene emulsion, a styrene-butadiene emulsion, an ethylene-vinyl acetate emulsion, an emulsion, and versatic acid acrylic acid. As the silicone oil, dimethyl silicone oil and organic functional silicone oil (functional groups include amino, epoxy, mercapto, phenyl, long-chain alkyl, hydrogen, etc.) can be used. The dustproofing agent made of such a resin emulsion solution forms a hydrophobic coating on the surface of the pile.

[0044] In activity A430, control unit 210 outputs the presence or absence of a drug or the amount of the drug contained in substance 130, which is the acquired object. Control unit 210 generates a screen including the presence or absence of a drug contained in substance 130 or the amount of the drug contained in substance 130 and displays it on output unit 240, generates a file or the like including the presence or absence of a drug contained in substance 130 or the amount of the drug contained in substance 130 and stores it in storage unit 220, or generates a file or the like including the presence or absence of a drug contained in substance 130 or the amount of the drug contained in substance 130 and transmits it to another device via communication unit 250, thereby outputting the water content. The processing of activity A430 is an example of processing for outputting the result of estimation.

[0045] According to the process of the first modification, it is possible to properly estimate the presence or absence or amount of a drug contained in the substance 130, which is the target object. Also, the result of the estimation can be output on a screen or the like.

[0046] (Variation 2) Modification 2 of embodiment 1 will be described. In modification 2, differences from embodiment 1 will be described. Modification 2 is a modification of part of the processing of embodiment 1, and is included in embodiment 1 rather than being a different embodiment from embodiment 1. FIG. 5 is a diagram showing an example of a system configuration of an information processing system 1000 according to the second modification. The substance 130 in the second modification is placed on a conveyer belt and moves. In such a configuration, the imaging unit 120 in the second modification (hereinafter simply referred to as the imaging unit 120) is not provided on an aircraft, and may be included in the information processing system 1000 in any manner as long as it can photograph the substance 130 from above. The imaging unit 120 in the second modification has its own control unit, memory, communication unit, etc. The control unit is a CPU, etc. The memory stores programs and data used by the control unit when executing processing. The communication unit connects the imaging unit 120 to the network 150.

[0047] In the case of the configuration shown in FIG. 5, the information processing system 1000 may be provided with a sensor 500 that measures the inclination of the belt conveyor. When the information processing system 1000 is provided with a sensor 500 that measures the inclination of the belt conveyor, the control unit 210 of the second modification may obtain inclination information of the surface of the material 130 based on information from the sensor 500. Examples of the sensor 500 include a LiDAR sensor and a 3D gyro sensor. However, this does not limit the sensor 500. Any sensor may be used as long as it directly measures the inclination of the material 130 or measures the inclination of an object on which the material 130 is placed (the belt conveyor in the example of the second modification) to know the inclination of the material 130. Alternatively, three-dimensional data may be generated from a photographed image taken by the photographing unit 120 and measured. Alternatively, the material 130 may be photographed by another camera mounted on a drone or the like to obtain a photographed image. The control unit 210 may then obtain the inclination of the material 130 from the three-dimensional data generated using the photographed image. In such a configuration, the other camera is also an example of a sensor.

[0048] The second modification can also achieve the same effects as the first embodiment described above.

[0049] (Variation 3) Modification 3 of embodiment 1 will be described. In modification 3, differences from embodiment 1 will be described. Modification 3 is a modification of a part of the processing of embodiment 1, and is included in embodiment 1 rather than being a different embodiment from embodiment 1. Fig. 6 is an activity diagram showing an example of information processing in the PC 100 of the modified example 3. In Fig. 6, the same reference numerals are used for the same parts as those in the information processing in the activity diagram of Fig. 3.

[0050] In the activity A610, the control unit 210 of the modified example 3 (hereinafter, simply referred to as the control unit 210) acquires information on the position of the light source relative to the substance 130. The sun will be described as an example of a light source. For example, the control unit 210 acquires date and time information and location information of the spectrum information included in the attribute information of the spectrum information used in the activity A300. Then, the control unit 210 acquires information on the position of the sun at the date and time indicated by the date and time information of the position indicated by the location information, based on the location information and date and time information, for the external system. The information on the position of the sun is either or both of information on the altitude of the sun relative to the object and information on the orientation of the sun relative to the object. Also, information obtained from either or both of information on the altitude of the sun relative to the object and information on the orientation of the sun relative to the object may be included in the information on the position of the sun. The processing of the activity A610 is an example of processing for acquiring information on the position of the light source relative to the substance 130, which is the object.

[0051] Other examples of light sources include light bulbs, fluorescent lights, lamps, LEDs (Light Emitting Diodes), etc. When the light source is a light bulb, fluorescent light, lamp, LED, etc., the control unit 210 may acquire information on the position of the preset light bulb, fluorescent light, lamp, LED, etc. from a predetermined device, or may acquire information that is preset in a predetermined file or the like stored in the storage unit 220, etc. Furthermore, when the imaging unit 120 includes light sources such as light bulbs, fluorescent lights, lamps, LEDs, etc. in the imaging range, the control unit 210 may specify information on the position of the light source from the light source included in the video captured by the imaging unit 120.

[0052] The order of processing activity A300 and activity A610 does not matter. Activity A300 may precede activity A610, or activity A300 may follow activity A610. Activity A300 and activity A610 may be executed simultaneously. However, control unit 210 acquires information on the optical characteristics and the position of the light source measured at the same date and time based on date and time information, etc.

[0053] In activity A620, control unit 210 acquires a trained model of modified example 3 (hereinafter simply referred to as trained model) from storage unit 220 or the like, and inputs the optical properties of substance 130 determined in activity A300 and information on the position of the light source relative to substance 130 determined in activity A610 to the acquired trained model. Here, the trained model is a trained model trained using the optical properties of substance 130 and information on the position of the light source relative to substance 130 as input data, and the water content of substance 130 as output data. Control unit 210 acquires the water content output from the trained model as an estimated value. The processing of activity A620 is an example of processing for estimating the water content of substance 130, which is an object, based on the optical properties and information on the position of the light source. By carrying out such processing, the water content, etc., of the substance 130, which is the target object, can be appropriately estimated.

[0054] In activity A630, the control unit 210 outputs the acquired water content. The control unit 210 outputs the water content by generating a screen including the water content and displaying it on the output unit 240, generating a file or the like including the water content and storing it in the storage unit 220, or generating a file or the like including the water content and transmitting it to another device via the communication unit 250.

[0055] The third modification can also achieve the same effects as the first embodiment described above.

[0056] (Variation 4) Modification 4 of embodiment 1 will be described. In modification 4, differences from embodiment 1 will be described. Modification 4 is a modification of part of the processing of embodiment 1, and is included in embodiment 1 rather than being a different embodiment from embodiment 1. Fig. 7 is an activity diagram showing an example of information processing in the PC 100 of Modification 4. In Fig. 7, the same reference numerals are used for the same parts as those in the information processing in the activity diagram of Fig. 3.

[0057] In activity A720, the control unit 210 of modified example 4 (hereinafter simply referred to as the control unit 210) acquires the trained model of modified example 4 (hereinafter simply referred to as the trained model) from the storage unit 220 or the like, and inputs the optical properties of the substance 130 obtained in activity A300 and the information on the position of the light source relative to the substance 130 obtained in activity A610 to the acquired trained model. Here, the trained model is a trained model trained with the optical properties of the substance 130 and the information on the position of the light source relative to the substance 130 as input data, and the presence or absence of a drug in the substance 130 or the amount of the drug as output data. The control unit 210 acquires the presence or absence of a drug in the substance 130, which is the object, or the amount of the drug output from the trained model as an estimated value. The processing of activity A720 is an example of a processing for estimating the presence or absence of a drug in the substance 130, which is the object, or the amount of the drug.

[0058] In activity A730, the control unit 210 outputs the presence or absence of a drug or the amount of the drug contained in the substance 130, which is the acquired object. The control unit 210 generates a screen including the presence or absence of a drug contained in the substance 130 or the amount of the drug contained, and displays it on the output unit 240, generates a file or the like including the presence or absence of a drug contained in the substance 130 or the amount of the drug contained, and stores it in the storage unit 220, or generates a file or the like including the presence or absence of a drug contained in the substance 130 or the amount of the drug contained, and transmits it to another device via the communication unit 250, thereby outputting the presence or absence of a drug contained or the amount of the drug. The processing of activity A730 is an example of processing for outputting the result of estimation.

[0059] According to the process of the fourth modification, it is possible to properly estimate the presence or absence or amount of a drug contained in the substance 130, which is the target object. In addition, the result of the estimation can be output on a screen or the like.

[0060] (Variation 5) Modification 5 of embodiment 1 will be described. In modification 5, differences from embodiment 1 will be described. Modification 5 is a modification of a part of the processing of embodiment 1, and is included in embodiment 1 rather than being a different embodiment from embodiment 1. The above-described first embodiment and a plurality of modified examples may be combined in any combination. For example, the first embodiment and modified example 3 may be combined, or modified example 1 and modified example 4 may be combined. For example, when the first embodiment and modified example 3 are combined, the control unit 210 of modified example 5 (hereinafter, simply referred to as the control unit 210) acquires a trained model from the storage unit 220 or the like, and inputs the optical properties of the material 130 obtained in activity A300, the information on the inclination of the surface of the material 130 obtained in activity A310, and the information on the position of the light source relative to the material 130 obtained in activity A610 to the acquired trained model. Here, the trained model is a trained model trained with the optical properties of the material 130, the information on the inclination of the surface of the material 130, and the information on the position of the light source relative to the material 130 as input data, and the water content of the material 130 as output data. The control unit 210 acquires the water content output from the trained model as an estimated value.

[0061] As described above, the tilt information is either or both of the slope direction and the slope angle of the object (material 130). The tilt information may also include information calculated from either or both of the slope direction and the slope angle of the object. The light source position information is either or both of the altitude information of the light source relative to the object and the orientation information of the light source relative to the object. The light source position information may also include information calculated from either or both of the altitude information of the light source relative to the object and the orientation information of the light source relative to the object.

[0062] Here, the sun will be taken as an example of a light source. More preferably, the control unit 210 obtains the solar incidence angle with respect to the object from the slope direction of the object, the slope angle of the object, the information of the altitude of the sun with respect to the object, and the information of the orientation of the sun with respect to the object. Alternatively, the control unit 210 obtains the light source incidence angle with respect to the object from the information of the altitude of the light source with respect to the object and the information of the orientation of the light source with respect to the object. Then, the control unit 210 may train a model using this solar incidence angle or light source incidence angle to generate a trained model. That is, the control unit 210 inputs the optical properties of the material 130 and the solar incidence angle or light source incidence angle with respect to the material 130 to the trained model. Here, the trained model is a trained model trained with the optical properties of the material 130 and the solar incidence angle or light source incidence angle with respect to the material 130 as input data, and the water content of the material 130 as output data. The control unit 210 acquires the water content output from the trained model as an estimated value.

[0063] Furthermore, the control unit 210 may acquire information on the control of the light amount of the photographing unit 120 from the photographing unit 120 or the flying object 110, etc., and use the information on the control of the light amount to learn a model and generate a learned model. An example of the information on the control of the light amount is the exposure time of the photographing unit 120. In the following, for the sake of simplicity, the exposure time of the photographing unit 120 is used as the information on the control of the light amount. The control unit 210 inputs the optical properties of the material 130, the solar incidence angle or the light source incidence angle to the material 130, and the exposure time to the learned model. Here, the learned model is a learned model that has been learned using the optical properties of the material 130, the solar incidence angle or the light source incidence angle to the material 130, and the exposure time as input data, and the water content of the material 130 as output data. The control unit 210 acquires the water content output from the learned model as an estimated value.

[0064] Furthermore, the control unit 210 may acquire the amount of global solar radiation at the location where the material 130 is placed, and may use this amount of global solar radiation to train a model and generate a trained model. For example, the control unit 210 transmits the location information and the shooting date and time to a predetermined other system, and acquires the amount of global solar radiation at the location indicated by the location information and at the date and time indicated by the shooting date and time from the other system. The control unit 210 inputs the optical properties of the material 130, the solar incidence angle or the light source incidence angle with respect to the material 130, the exposure time, and the amount of global solar radiation to the trained model. Here, the trained model is a trained model trained using the optical properties of the material 130, the solar incidence angle or the light source incidence angle with respect to the material 130, the exposure time, and the amount of global solar radiation as input data, and the water content of the material 130 as output data. The control unit 210 acquires the water content output from the trained model as an estimated value.

[0065] The processing of the fifth modification can also achieve the same effects as those of the first embodiment.

[0066] Although the embodiments of the present invention have been described above, these are merely examples of the present invention, and various configurations other than those described above can be adopted. Furthermore, the present invention is not limited to the above-described embodiments, and modifications and improvements within the scope of the present invention are included in the present invention. [Explanation of symbols]

[0067] 110: Flying object 120: Photography Department 130: Substance 150: Network 210: Control section 220: Storage section 230: Input section 240: Output section 250: Communications Department 260: Communications Department 310: Control section 500: Sensor 1000: Information processing systems

Claims

1. An information processing system, Acquire the optical properties of the object, Obtaining information about the inclination of a surface of the object; estimating a water content of the object based on the optical property and the tilt information; Information processing system.

2. 2. The information processing system according to claim 1, Inputting the optical characteristics and the tilt information into a trained model; The trained model is a trained model trained using optical properties of an object and information on the inclination of the surface of the object as input data and water content of the object as output data, Obtaining the water content output from the trained model as an estimation result; Information processing system.

3. An information processing system, Acquire the optical properties of the object, Obtaining information about the inclination of a surface of the object; Estimating the presence or absence of a drug or the amount of the drug contained in the object based on the optical characteristics and the tilt information. Information processing system.

4. 4. The information processing system according to claim 3, Inputting the optical characteristics and the tilt information into a trained model; The trained model is a trained model trained using the optical characteristics of an object and information on the inclination of the surface of the object as input data, and the presence or absence or content of a drug in the object as output data, Obtaining the presence or absence or amount of a drug in the object output from the trained model as an estimation result; Information processing system.

5. 2. The information processing system according to claim 1, The inclination information is either or both of the slope direction and the slope angle of the object. Information processing system.

6. 6. The information processing system according to claim 5, acquiring the tilt information from a sensor; Information processing system.

7. An information processing system, Acquire the optical properties of the object, acquiring information about a position of a light source relative to the object; estimating the water content of the object based on the optical characteristics and the information on the position of the light source; Information processing system.

8. 8. The information processing system according to claim 7, Inputting the optical characteristics and the information on the position of the light source into a trained model; The trained model is a trained model trained using optical characteristics of an object and information on the position of a light source relative to the object as input data and water content of the object as output data, Obtaining the water content output from the trained model as an estimation result; Information processing system.

9. An information processing system, Acquire the optical properties of the object, acquiring information about a position of a light source relative to the object; Estimating the presence or absence or amount of a drug contained in the object based on the optical characteristics and information on the position of the light source. Information processing system.

10. 10. The information processing system according to claim 9, Inputting the optical characteristics and the information on the position of the light source into a trained model; The trained model is a trained model trained using the optical characteristics of an object and information on the position of a light source relative to the object as input data, and the presence or absence of a drug in the object or the amount of the drug as output data, Obtaining the presence or absence or amount of a drug in the object output from the trained model as an estimation result; Information processing system.

11. 8. The information processing system according to claim 7, The information on the position of the light source is either or both of information on the altitude of the light source relative to the object and information on the orientation of the light source relative to the object. Information processing system.

12. 2. The information processing system according to claim 1, Output the estimation results, Information processing system.

13. An information processing method executed by an information processing system, comprising: Acquire the optical properties of the object, Obtaining information about the inclination of a surface of the object; estimating a water content of the object based on the optical property and the tilt information; Information processing methods.

14. An information processing method executed by an information processing system, comprising: Acquire the optical properties of the object, Obtaining information about the inclination of a surface of the object; Estimating the presence or absence of a drug or the amount of the drug contained in the object based on the optical characteristics and the tilt information. Information processing methods.

15. An information processing method executed by an information processing system, comprising: Acquire the optical properties of the object, acquiring information about a position of a light source relative to the object; estimating the water content of the object based on the optical characteristics and the information on the position of the light source; Information processing methods.

16. An information processing method executed by an information processing system, comprising: Acquire the optical properties of the object, acquiring information about a position of a light source relative to the object; Estimating the presence or absence or amount of a drug contained in the object based on the optical characteristics and information on the position of the light source. Information processing methods.

17. A program, Computer, A program for causing the information processing system according to any one of claims 1 to 12 to function as such.

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