Intelligent seeding method, device, equipment, storage medium and computer program product

Abstract

The present application discloses an intelligent sowing method, device, equipment, storage medium and computer program product, which relates to the field of intelligent agricultural technology. The method includes: determining the seed type and seed maturity of the seeds to be sown according to the seed image of the seeds to be sown; determining the target sowing seeds from the seeds to be sown based on the seed type and seed maturity, and the target planting strategy corresponding to the target sowing seeds; determining the optimal planting spacing and regional sowing row number of the target sowing seeds according to the target planting strategy; bonding the target sowing seeds to the seed carrier material through the seed bonding and rolling process; laying the seed carrier material to the front sowing area based on the optimal planting spacing and regional sowing row number by the sowing equipment to plant the target sowing seeds. The application of the above technical solution solves the technical problem that the sowing method in the prior art has a low degree of automation, resulting in low seed sowing efficiency.

Description

Technical Field

[0001] The present application relates to the field of intelligent agricultural technology, and in particular to intelligent sowing methods, devices, equipment, storage media and computer program products. Background Art

[0002] In recent years, with the continuous development of agriculture, the demand for intelligent and automated seeding technology has become stronger and stronger. It plays a vital role in the development of my country's modern agriculture. Intelligent seeding has become the development trend of the future seeding market. In the existing scheme, seeding is usually carried out by manually operating the seeding machine. However, when the sowing workload is large, relying on manual operation will lead to low seed sowing efficiency.

[0003] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The main purpose of this application is to provide an intelligent sowing method, device, equipment, storage medium and computer program product, aiming to solve the technical problem that the sowing method in the prior art has a low degree of automation, resulting in low seed sowing efficiency.

[0005] To achieve the above objectives, the present application proposes an intelligent seeding method, which comprises:

[0006] Determining the seed type and seed maturity of the seeds to be sown according to the seed images of the seeds to be sown;

[0007] Determining target sowing seeds from the seeds to be sown based on the seed type and the seed maturity, and a target planting strategy corresponding to the target sowing seeds;

[0008] Determine the optimal planting spacing and regional sowing row number of the target sowing seeds according to the target planting strategy;

[0009] Adhere the target sowing seeds to the seed carrier material through a seed adhesive and rolling process;

[0010] The seed carrier material is spread to the front sowing area by sowing equipment based on the optimal planting spacing and the number of sowing rows in the area to plant the target sowing seeds.

[0011] In one embodiment, the step of determining the seed type and seed maturity of the seeds to be sown according to the seed image of the seeds to be sown comprises:

[0012] Extracting shape features and color features of the seeds to be sown from the seed images of the seeds to be sown;

[0013] Obtaining the standard shape features corresponding to each template seed through the standard seed images corresponding to several template seeds;

[0014] Determine a target template seed that matches the seed to be sown based on the shape feature and the standard shape feature, and determine a target seed type of the target template seed as the seed type of the seed to be sown;

[0015] Find all seed color images corresponding to the target seed type, the seed color image is used to characterize the maturity of the target template seed;

[0016] The seed maturity of the seeds to be sown is determined based on the color feature and the seed color image.

[0017] In one embodiment, the step of determining the seed maturity of the seeds to be sown based on the color feature and the seed color image comprises:

[0018] Obtaining the standard color features corresponding to the target template seed at different maturity levels through the seed color image;

[0019] Determining a similarity between the color feature and the standard color feature;

[0020] Determining a target color feature that matches the color feature from the standard color features based on the similarity;

[0021] The seed maturity of the seeds to be sown is determined based on the target color characteristics.

[0022] In one embodiment, before the step of laying the seed carrier material to the front sowing area by the sowing equipment based on the optimal planting spacing and the number of sowing rows in the area to plant the target sowing seeds, the step includes:

[0023] Collecting soil information of the current sowing area, the soil information includes: soil temperature, soil moisture and soil density;

[0024] Determining target soil information required for target sowing seeds according to the seed type;

[0025] Determine, based on the soil information and the target soil information, a planting attribute value of the target sowing seed at different soil depths in the current sowing area, wherein the planting attribute value is used to characterize the suitability of the target sowing seed for planting at each soil depth;

[0026] Determining the optimal planting depth of the target sowing seed in the current sowing area based on the planting attribute value;

[0027] The step of laying the seed carrier material to the front sowing area by the sowing equipment based on the optimal planting spacing and the number of sowing rows in the area to plant the target sowing seeds includes:

[0028] The seed carrier material is spread to the front sowing area by sowing equipment based on the optimal planting spacing, the number of sowing rows in the area and the optimal planting depth to plant the target sowing seeds.

[0029] In one embodiment, after the step of laying the seed carrier material to the front sowing area by the sowing equipment based on the optimal planting spacing, the number of sowing rows in the area and the optimal planting depth to plant the target sowing seeds, it also includes:

[0030] During the laying process, obtaining obstacle information around the sowing equipment in real time;

[0031] Determine a target planting position of the target sowing seeds in the current sowing area;

[0032] generating an obstacle map of the current sowing area based on the obstacle information and the target planting position;

[0033] Generate a sowing driving path corresponding to the sowing equipment based on the obstacle map and the target planting position;

[0034] The seed carrier material is laid to the front sowing area by the sowing equipment based on the sowing travel path, the optimal planting spacing, the number of sowing rows in the area and the optimal planting depth to plant the target sowing seeds.

[0035] In one embodiment, the step of generating an obstacle map of the current sowing area based on the obstacle information and the target planting position includes:

[0036] Determine all obstacles in the current sowing area according to the obstacle information;

[0037] Determining the obstacle probability corresponding to each obstacle object based on the target planting position;

[0038] An obstacle map of the current sowing area is generated based on the obstacle probability.

[0039] In addition, to achieve the above purpose, the present application also proposes an intelligent seeding device, which includes:

[0040] A seed information determination module, used to determine the seed type and seed maturity of the seeds to be sown according to the seed image of the seeds to be sown;

[0041] A planting strategy determination module, used to determine a target sowing seed from the seeds to be sown based on the seed type and the seed maturity, and a target planting strategy corresponding to the target sowing seed;

[0042] A sowing information determination module, used to determine the optimal planting spacing of the target sowing seeds and the number of regional sowing rows according to the target planting strategy;

[0043] A seed bonding module, used for bonding the target sowing seeds to a seed carrier material through a seed bonding and rolling process;

[0044] The seed planting module is used to spread the seed carrier material to the front sowing area based on the optimal planting spacing and the number of sowing rows in the area through sowing equipment to plant the target sowing seeds.

[0045] In addition, to achieve the above objectives, the present application also proposes an intelligent seeding device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the intelligent seeding method described above.

[0046] In addition, to achieve the above objectives, the present application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the intelligent seeding method described above are implemented.

[0047] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the intelligent seeding method described above are implemented.

[0048] The present application provides an intelligent sowing method, which discloses determining the seed type and seed maturity of seeds to be sown according to seed images of the seeds to be sown; determining target sowing seeds from the seeds to be sown based on the seed type and seed maturity, and the target planting strategy corresponding to the target sowing seeds; determining the optimal planting spacing and regional sowing row number of the target sowing seeds according to the target planting strategy; bonding the target sowing seeds to the seed carrier material through a seed bonding and rolling process; laying the seed carrier material to the front sowing area based on the optimal planting spacing and regional sowing row number by sowing equipment to plant the target sowing seeds; compared with the prior art, which usually sows by manually operating a seeder, when the sowing workload is large, it will lead to low seed sowing efficiency. Since the present invention determines the target sowing seeds according to the seed type and seed maturity of the seeds to be sown, and plants the target sowing seeds based on the optimal planting spacing and regional sowing row number of the target sowing seeds by sowing equipment, the technical problem of low automation in the prior art and low seed sowing efficiency is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0050] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0051] Figure 1 A schematic diagram of a process flow provided for the first embodiment of the intelligent seeding method of the present application;

[0052] Figure 2 A schematic diagram of the process flow provided for the second embodiment of the intelligent seeding method of the present application;

[0053] Figure 3 A schematic diagram of the process flow provided for the third embodiment of the intelligent seeding method of the present application;

[0054] Figure 4 This is a schematic diagram of the module structure of the intelligent seeding device according to an embodiment of the present application;

[0055] Figure 5 Schematic diagram of the device structure of the hardware operating environment involved in the intelligent seeding method in the embodiment of the present application.

[0056] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0057] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0058] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0059] The main solution of the embodiment of the present application is: determine the seed type and seed maturity of the seeds to be sown according to the seed image of the seeds to be sown; determine the target sowing seeds from the seeds to be sown based on the seed type and the seed maturity, and the target planting strategy corresponding to the target sowing seeds; determine the optimal planting spacing and the number of regional sowing rows of the target sowing seeds according to the target planting strategy; bond the target sowing seeds to the seed carrier material through a seed bonding and rolling process; and lay the seed carrier material to the front sowing area based on the optimal planting spacing and the number of regional sowing rows by sowing equipment to plant the target sowing seeds.

[0060] Since in the prior art, sowing is usually performed by manually operating a seeder, when the sowing workload is large, the seed sowing efficiency will be low.

[0061] The present application provides a solution that allows target sowing seeds to be determined based on the seed type and seed maturity of the seeds to be sown, and to be planted by sowing equipment based on the target sowing seeds' optimal planting spacing and regional sowing row numbers, thereby solving the technical problem in the prior art that the sowing method has a low degree of automation, resulting in low seed sowing efficiency.

[0062] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, an intelligent seeding device, etc. The following takes the intelligent seeding device as an example (hereinafter referred to as the device) to illustrate this embodiment and the following embodiments.

[0063] Based on this, the embodiment of the present application provides an intelligent seeding method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the intelligent seeding method of the present application.

[0064] In this embodiment, the intelligent seeding method includes steps S10 to S40:

[0065] Step S10: determining the seed type and seed maturity of the seeds to be sown according to the seed image of the seeds to be sown.

[0066] It should be noted that the above-mentioned seeds to be sown can be any seeds that need to be sown, wherein the seed types of the seeds to be sown in this embodiment can include but are not limited to rice, corn, etc.

[0067] It can be understood that the above-mentioned seed maturity can be a value used to characterize the maturity degree of seeds to be sown.

[0068] In actual applications, since the environmental conditions suitable for the growth of different types of seeds and seeds of different maturity levels are usually different, the equipment can collect seed images of all seeds to be sown through an image acquisition device, and determine the types and maturity of all seeds to be sown based on these seed images, so as to facilitate the subsequent classification of these seeds and plant these seeds according to the suitable planting conditions of different categories of seeds.

[0069] Furthermore, the step S10 includes:

[0070] Step S101: extracting shape features and color features of the seeds to be sown from the seed images of the seeds to be sown.

[0071] It should be noted that the above shape feature can be a feature used to characterize the shape of the seeds to be sown; correspondingly, the above color feature can be a feature used to characterize the color of the seeds to be sown, wherein a color histogram can be used to describe the color feature in this embodiment. In this embodiment, the device can extract features of the seed image of the seeds to be sown by image recognition technology, so as to extract the color features and shape features of the seeds to be sown from the seed image of the seeds to be sown.

[0072] Step S102: obtaining standard shape features corresponding to each template seed through standard seed images corresponding to a number of template seeds.

[0073] It should be understood that the template seed is a seed that is representative of the various types of seeds in terms of shape, color, etc. Correspondingly, the standard seed image may be an image corresponding to the template seed.

[0074] It can be understood that the above-mentioned standard shape features can be features used to characterize the shape of the template seed.

[0075] Step S103: determining a target template seed that matches the seed to be sown based on the shape feature and the standard shape feature, and determining a target seed type of the target template seed as the seed type of the seed to be sown.

[0076] It should be noted that the target template seed may be a template seed having the same or similar shape characteristics as the seed to be sown. Accordingly, the target seed type may be a seed type corresponding to the target template seed.

[0077] In a specific implementation. The device can extract features of the standard seed images corresponding to all template seeds through image recognition technology, so that the shape features corresponding to each template seed can be extracted from the standard seed image to obtain the standard shape features. Then, the device can match the shape features of the seeds to be sown with the standard shape features of each template seed to match and obtain the target template seed with the highest degree of matching with the seeds to be sown from each template seed. Among them, since the shape of the target template seed is similar to the shape of the seed to be sown, the device can determine the seed type of the target template seed as the seed type of the seed to be sown. In addition, in order to improve the accuracy of determining the seed type of the seeds to be sown, the present solution can also extract the size features of the seeds to be sown and the template seeds from the seed images of the seeds to be sown and the template seeds, and further match the seeds to be sown and the template seeds based on the size features to accurately determine the seed type of the seeds to be sown, so that the subsequent sowing can be based on the seed type of the seeds to be sown. Adopt an accurate planting strategy for sowing, which is conducive to improving the survival rate of the seeds.

[0078] Step S104: searching for all seed color images corresponding to the target seed type, wherein the seed color image is used to characterize the maturity of the target template seed.

[0079] It should be understood that the seed color image may be an image that represents the maturity of the seed by color. In this embodiment, for different types of seeds, multiple seed color images representing their maturity by color are pre-mapped and stored in the database. After the device determines the seed type of the seeds to be sown as the target seed type, it can search for all seed color images corresponding to the target seed type from the database.

[0080] Step S105: determining the seed maturity of the seeds to be sown based on the color feature and the seed color image.

[0081] Specifically, the step S105 includes: obtaining the standard color features corresponding to the target template seeds at different maturity levels through the seed color image; determining the similarity between the color features and the standard color features; determining the target color features matching the color features from the standard color features based on the similarity; and determining the seed maturity of the seeds to be sown based on the target color features.

[0082] It should be noted that the above standard color features may be color features corresponding to target template seeds at different degrees of maturity; correspondingly, the above target color features may be color features with the highest similarity to the color features of the seeds to be sown. In practical applications, seeds with lower maturity are usually green in color, while seeds with higher maturity are usually yellow in color. Therefore, the device can determine the current maturity of the seeds based on the color features of the seeds.

[0083] It can be understood that the database in this embodiment can map and store the seed names of different types of seeds, all seed color images corresponding to the seed names, and the seed maturity corresponding to various sub-color images. Therefore, after the device determines the target color feature with the highest similarity to the color feature of the seeds to be sown, it can determine the target seed color image corresponding to the target color feature according to the mapping relationship table stored in the database, so that the seed maturity corresponding to the target seed color image can be determined as the seed maturity of the seeds to be sown.

[0084] In a specific implementation, the device can first perform feature extraction on the seed color image to extract the standard color features corresponding to different maturity levels of the target template seeds from the seed color image, and compare the standard color features with the color features of the seeds to be sown, calculate the similarity between the color features of the seeds to be sown and the standard color features, and then determine the target color features with the highest similarity to the color features of the seeds to be sown from the standard color features based on the similarity, so that the seed maturity of the seeds to be sown can be determined according to the target seed color image corresponding to the target color features.

[0085] Step S20: determining target sowing seeds from the seeds to be sown based on the seed type and the seed maturity, and a target planting strategy corresponding to the target sowing seeds.

[0086] It should be noted that the target sowing seeds mentioned above may be seeds of the same seed type and similar maturity among the seeds to be sown; correspondingly, the target planting strategy mentioned above may be a strategy adopted for planting the target sowing seeds.

[0087] In this embodiment, in order to improve the success rate of seed planting, the device can adopt different planting strategies for different types of seeds and seeds of different maturity. Specifically, the device can classify all seeds to be sown according to the seed type and maturity of the seeds to be sown in advance, and classify seeds of the same type and the same or similar maturity into one category. At the same time, the device can also screen the seeds to be sown, remove dead or defective seeds from the seeds to be sown, and finally obtain the above-mentioned target sowing seeds.

[0088] Step S30: determining the optimal planting spacing and regional sowing row number of the target sowing seeds according to the target planting strategy.

[0089] It should be noted that the above-mentioned optimal planting spacing may be the most suitable planting spacing for the target sowing seeds; correspondingly, the above-mentioned number of sowing rows in the area may be the most suitable number of sowing rows for the target sowing seeds in the current area.

[0090] Step S40: bonding the target sowing seeds to the seed carrier material through a seed bonding and rolling process.

[0091] It should be noted that the above-mentioned seed bonding and rolling process can be a process of bonding seeds to seed carrier materials (such as paper, degradable mulch, etc.) using a special adhesive, and rolling and packaging the treated seed carrier materials. In practical applications, bonding seeds to seed carrier materials can protect seeds and improve sowing efficiency and uniformity. In addition, rolling and packaging the treated seed carrier materials can facilitate storage and transportation.

[0092] Step S50: using a sowing device to spread the seed carrier material to the front sowing area based on the optimal planting spacing and the number of sowing rows in the area to plant the target sowing seeds.

[0093] It is understandable that the above-mentioned sowing equipment can be a seeding machine for sowing, wherein the seeding machine can have functions such as fertilization in addition to the sowing function. In actual applications, a driving machine is provided inside the sowing equipment, and the sowing equipment can sow by running the driving machine. In this embodiment, the equipment can control the rotation angle of the stepper motor in the driving machine inside the seeding machine by setting a program to control the spacing during sowing, so that the seeding machine can sow at the optimal sowing spacing in the current sowing area.

[0094] In a specific implementation, before planting the target sowing seeds, a target planting strategy corresponding to the target sowing seeds can be generated based on the seed type and seed maturity of the target sowing seeds. Thereafter, when it is necessary to plant the target sowing seeds, the most suitable planting spacing and the most suitable number of sowing rows of the target sowing seeds in the current area can be determined based on the current planting area and the target planting strategy corresponding to the target sowing seeds, and the target sowing seeds can be bonded to the seed carrier material through the seed bonding and rolling process. At this time, the seed carrier material carries the target sowing seeds, and then the seeder can be controlled to lay the seed carrier material in the current area (such as a certain area in the rice field) based on the optimal planting spacing and the number of regional sowing rows to achieve the planting of the target sowing seeds. Thereafter, when the temperature, humidity and other conditions in the current area reach the germination conditions of the target sowing seeds in the seed carrier material, the target sowing seeds germinate and pierce the seed carrier material to germinate and grow, and then grow naturally in the rice field.

[0095] The present embodiment provides an intelligent sowing method, which discloses determining the seed type and seed maturity of the seeds to be sown according to the seed image of the seeds to be sown; determining the target sowing seeds from the seeds to be sown based on the seed type and seed maturity, and the target planting strategy corresponding to the target sowing seeds; determining the optimal planting spacing and regional sowing row number of the target sowing seeds according to the target planting strategy; bonding the target sowing seeds to the seed carrier material through a seed bonding and rolling process; laying the seed carrier material to the front sowing area based on the optimal planting spacing and regional sowing row number by sowing equipment to plant the target sowing seeds; compared with the prior art, which usually sows by manually operating a seeder, when the sowing workload is large, it will lead to low seed sowing efficiency. Since the present embodiment determines the target sowing seeds according to the seed type and seed maturity of the seeds to be sown, and plants the target sowing seeds based on the optimal planting spacing and regional sowing row number of the target sowing seeds by sowing equipment, it solves the technical problem of low automation of the sowing method in the prior art, resulting in low seed sowing efficiency.

[0096] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 2 , Figure 2 A flow chart of the second embodiment of the intelligent seeding method of the present application.

[0097] In this embodiment, before step S40, the intelligent seeding method further includes steps S301 to S304:

[0098] Step S301: collecting soil information of the current sowing area, wherein the soil information includes soil temperature, soil moisture and soil density.

[0099] It should be understood that the above-mentioned current sowing area may be an area for sowing seeds for the current planting target.

[0100] Step S302: Determine target soil information required for sowing the target seeds according to the seed type.

[0101] It should be noted that the above target soil information may be the most suitable soil information required for planting the seeds to be sown in the current sowing area and making them germinate. In this embodiment, the target soil information may include but is not limited to information such as optimal soil temperature, optimal soil moisture, and optimal soil density. In practical applications, since the soil conditions required for germination of different types of seeds are usually different, the embodiment may predetermine the optimal soil temperature, optimal soil moisture, and optimal soil density required for germination of different types of seeds through experiments, and then establish a mapping relationship table based on the seed type and the optimal soil temperature, optimal soil moisture, and optimal soil density required for germination, and store the mapping relationship table in a database.

[0102] Step S303: Determine the planting attribute values ​​of the target sowing seeds at different soil depths in the current sowing area based on the soil information and the target soil information, wherein the planting attribute values ​​are used to characterize the suitability of the target sowing seeds for being planted at each soil depth.

[0103] It should be noted that the above-mentioned planting attribute values ​​are values ​​used to characterize the suitability of planting the seeds to be sown at different soil depths in the current sowing area. In this embodiment, the planting attribute values ​​can be determined by the germination degree of the seeds when planted at different soil depths in the current sowing area. Generally speaking, when seeds are planted at different soil depths in the same area, the faster the germination speed and the faster the germination growth speed, the greater the planting attribute value of the seed at the current soil depth. Otherwise, the smaller the planting attribute value of the seed at the current soil depth.

[0104] In this embodiment, the device may pre-set a planting attribute value calculation formula, and calculate the planting attribute values ​​of different soil depths by using the formula, wherein the planting attribute value calculation formula may be:

[0105] Planting attribute value = {(soil temperature - optimal soil temperature) 2 + (soil moisture - optimum soil moisture) 2 +(soil density*10 -7 - Optimal soil density*10 -7 ) 2} / 3.

[0106] Step S304: determining the optimal planting depth of the target sowing seed in the current sowing area based on the planting attribute value.

[0107] It can be understood that the above-mentioned optimal planting depth can be the most suitable planting depth for the target sowing seeds in the current sowing area. In this embodiment, the soil depth with the maximum planting attribute value in the current sowing area can be determined as the optimal planting depth.

[0108] Accordingly, the step S40 includes:

[0109] Step S40': laying the seed carrier material to the front sowing area by sowing equipment based on the optimal planting spacing, the number of sowing rows in the area and the optimal planting depth to plant the target sowing seeds.

[0110] In a specific implementation, the device can collect soil information at a soil depth of 0-8 cm in the current sowing area. Specifically, the present embodiment can evenly divide the soil of 0-8 cm into four layers, and respectively collect the soil temperature, soil moisture and soil density of the four layers of soil to determine the soil information at different soil depths in the current sowing area, and then search the database for the optimal soil temperature, optimal soil moisture and optimal soil density required for the target sowing seeds in the current sowing area according to the seed type of the target sowing seeds. Then, based on the soil temperature, soil moisture and soil density at different soil depths, as well as the optimal soil temperature, optimal soil moisture and optimal soil density, the planting attribute value of each soil depth can be calculated by the above-mentioned planting attribute value calculation formula, and the soil depth with the largest planting attribute value is determined as the optimal planting depth of the target sowing seeds in the current sowing area. Finally, the seeder can be controlled to lay the seed carrier material bonded with the target sowing seeds to the front sowing area at the optimal planting depth, optimal planting spacing and number of regional sowing rows to plant the target sowing seeds. In this embodiment, the target seeds are sown at the optimal planting depth, optimal planting spacing and number of regional sowing rows, so as to improve the sowing accuracy and at the same time help to improve the survival rate of the sown seeds.

[0111] In this embodiment, the soil information of the current sowing area is collected, and the soil information includes: soil temperature, soil moisture and soil density; the target soil information required for the target sowing seeds is determined according to the seed type; the planting attribute values ​​of the target sowing seeds at different soil depths in the current sowing area are determined based on the soil information and the target soil information, and the planting attribute values ​​are used to characterize the suitability of the target sowing seeds to be planted at each soil depth; the optimal planting depth of the target sowing seeds in the current sowing area is determined based on the planting attribute values; the seed carrier material is laid to the front sowing area by the sowing equipment based on the optimal planting spacing, the number of regional sowing rows and the optimal planting depth to plant the target sowing seeds, thereby improving the sowing accuracy and facilitating the improvement of the survival rate of the seeds.

[0112] Based on the first embodiment and / or the second embodiment of the present application, in the third embodiment of the present application, the same or similar contents as those in the above embodiments can be referred to the above introduction, and will not be described in detail later. Figure 3 , Figure 3 This is a flow chart of the third embodiment of the intelligent seeding method of this application.

[0113] In this embodiment, after step S40, the intelligent seeding method further includes steps S501 to S505:

[0114] Step S501: During the laying process, obstacle information around the sowing equipment is obtained in real time.

[0115] It should be noted that the above obstacle information may be information such as the location and quantity of obstacles around the sowing device, and this embodiment does not limit this. In this embodiment, the device may collect environmental data around the sowing device through devices such as ultrasonic sensors or cameras, and identify obstacles around the sowing machine through the collected environmental data, and determine the locations of these obstacles, etc., to obtain the above obstacle information.

[0116] Step S502: Determine a target planting position of the target sowing seeds in the current sowing area.

[0117] It can be understood that the above-mentioned target planting positions can be all positions in the current sowing area where target sowing seeds need to be planted.

[0118] Step S503: generating an obstacle map of the current sowing area based on the obstacle information and the target planting position.

[0119] It should be noted that the above obstacle map may be a map used to characterize the distribution of obstacles in the current sowing area.

[0120] Specifically, the step S503 includes: determining all obstacle objects in the current sowing area according to the obstacle information; determining the obstacle probability corresponding to each obstacle object based on the target planting position; and generating an obstacle map of the current sowing area based on the obstacle probability.

[0121] It should be noted that the above obstacle probability may be the probability of the sowing equipment colliding with an obstacle when it travels to the target planting position for sowing. In this embodiment, the probability of the sowing equipment colliding with an obstacle, i.e., the obstacle probability, may be represented in the obstacle map by different color depths, wherein the greater the obstacle probability of an obstacle object, the darker the color of the obstacle object in the obstacle map; and the smaller the obstacle probability of the obstacle object, the lighter the color of the obstacle object in the obstacle map.

[0122] In a specific implementation, the device can determine the current positions of all obstacles, and determine the distance between each obstacle and the target planting positions around it based on the current positions of the obstacle objects. The closer the distance between the obstacle object and the target planting positions around it, the greater the obstacle probability of the obstacle object. Otherwise, the smaller the obstacle probability of the obstacle object. Based on this, the device can calculate and obtain the obstacle probability corresponding to each obstacle object around the sowing equipment, and generate an obstacle map of the current sowing area based on the obstacle probability.

[0123] Step S504: generating a sowing travel path corresponding to the sowing equipment based on the obstacle map and the target planting position.

[0124] It should be noted that the above-mentioned sowing driving path can be the path that the sowing equipment drives when sowing in the current sowing area. In practical applications, the equipment can regularize the sowing driving path of the sowing equipment according to the target planting position and the location of each obstacle object in the obstacle map, obtain several driving paths, and calculate the driving cost of each driving path according to the obstacle probability of all obstacle objects around each target planting position in each driving path, and then the driving path with the minimum driving cost can be determined as the final sowing driving path.

[0125] Step S505: The seed carrier material is laid to the front sowing area by the sowing equipment based on the sowing travel path, the optimal planting spacing, the number of sowing rows in the area and the optimal planting depth to plant the target sowing seeds.

[0126] In a specific implementation, after the device determines the sowing driving path with the minimum driving cost, it can control the sowing machine to drive along the sowing driving path, and lay the seed carrier material with the target sowing seeds bonded to the front sowing area with the optimal planting spacing, regional sowing row number and optimal planting depth, so as to sow in the current sowing area. This embodiment controls the sowing equipment to drive in the current sowing area along the sowing driving path with the minimum cost, so as to prevent the sowing equipment from colliding with obstacles in the current sowing area during the sowing process to affect the sowing, thereby improving the sowing efficiency.

[0127] In this embodiment, it is disclosed that during the laying process, obstacle information around the sowing equipment is obtained in real time; the target planting position of the target sowing seeds in the current sowing area is determined; an obstacle map of the current sowing area is generated based on the obstacle information and the target planting position; a sowing travel path corresponding to the sowing equipment is generated based on the obstacle map and the target planting position; the seed carrier material is laid to the front sowing area by the sowing equipment based on the sowing travel path, the optimal planting spacing, the number of regional sowing rows and the optimal planting depth to plant the target sowing seeds, thereby improving the sowing accuracy and sowing efficiency.

[0128] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the intelligent seeding method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0129] This application also provides an intelligent seeding device, please refer to Figure 4 , the intelligent seeding device comprises:

[0130] A seed information determination module 10, used to determine the seed type and seed maturity of the seeds to be sown according to the seed image of the seeds to be sown;

[0131] A planting strategy determination module 20, for determining a target sowing seed from the seeds to be sown based on the seed type and the seed maturity, and a target planting strategy corresponding to the target sowing seed;

[0132] A sowing information determination module 30, for determining the optimal planting spacing and the number of regional sowing rows of the target sowing seeds according to the target planting strategy;

[0133] A seed bonding module 40, for bonding the target sowing seeds to a seed carrier material through a seed bonding and rolling process;

[0134] The seed planting module 50 is used to spread the seed carrier material to the front sowing area based on the optimal planting spacing and the number of sowing rows in the area through sowing equipment to plant the target sowing seeds.

[0135] The intelligent sowing device provided by the present application adopts the intelligent sowing method in the above embodiment, which can solve the technical problem that the sowing method in the prior art has a low degree of automation, resulting in low seed sowing efficiency. Compared with the prior art, the beneficial effects of the intelligent sowing device provided by the present application are the same as the beneficial effects of the intelligent sowing method provided by the above embodiment, and other technical features in the intelligent sowing device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0136] The present application provides an intelligent sowing device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the intelligent sowing method in the above-mentioned embodiment one.

[0137] Reference below Figure 5 , which shows a schematic diagram of the structure of the intelligent seeding device suitable for implementing the embodiment of the present application. The intelligent seeding device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The intelligent seeding device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0138] like Figure 5As shown, the intelligent seeding device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the intelligent seeding device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the intelligent seeding device to communicate wirelessly or wired with other devices to exchange data. Although the figure shows an intelligent seeding device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or provided instead.

[0139] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0140] The intelligent sowing device provided by the present application adopts the intelligent sowing method in the above embodiment to solve the technical problem of intelligent sowing. Compared with the prior art, the beneficial effects of the intelligent sowing device provided by the present application are the same as the beneficial effects of the intelligent sowing method provided by the above embodiment, and other technical features in the intelligent sowing device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0141] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0142] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0143] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the intelligent seeding method in the above-mentioned embodiment.

[0144] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0145] The computer-readable storage medium may be included in the intelligent seeding device; or may exist independently without being assembled into the intelligent seeding device.

[0146] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the intelligent sowing device, the intelligent sowing device: determines the seed type and seed maturity of the seeds to be sown according to the seed image of the seeds to be sown; determines the target sowing seeds from the seeds to be sown based on the seed type and the seed maturity, and the target planting strategy corresponding to the target sowing seeds; determines the optimal planting spacing and the number of regional sowing rows for the target sowing seeds according to the target planting strategy; adheres the target sowing seeds to the seed carrier material through a seed bonding and rolling process; and spreads the seed carrier material to the front sowing area through the sowing device based on the optimal planting spacing and the number of regional sowing rows to plant the target sowing seeds.

[0147] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0148] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0149] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0150] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned intelligent sowing method, and can solve the technical problem that the sowing method in the prior art has a low degree of automation, resulting in low seed sowing efficiency. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the intelligent sowing method provided by the above-mentioned embodiment, and will not be repeated here.

[0151] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned intelligent seeding method when executed by a processor.

[0152] The computer program product provided by the present application can solve the technical problem that the sowing method in the prior art has a low degree of automation, resulting in low seed sowing efficiency. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as those of the intelligent sowing method provided by the above embodiment, and will not be described in detail here.

[0153] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. An intelligent sowing method, characterized in that: The method includes: Determining the seed type and seed maturity of the seeds to be sown according to the seed images of the seeds to be sown; Determining target sowing seeds from the seeds to be sown based on the seed type and the seed maturity, and a target planting strategy corresponding to the target sowing seeds; Determine the optimal planting spacing and regional sowing row number of the target sowing seeds according to the target planting strategy; Adhere the target sowing seeds to the seed carrier material through a seed adhesive and rolling process; The seed carrier material is laid to the front sowing area by sowing equipment based on the optimal planting spacing and the number of sowing rows in the area to plant the target sowing seeds; Before the step of laying the seed carrier material to the front sowing area by the sowing equipment based on the optimal planting spacing and the number of sowing rows in the area to plant the target sowing seeds, the method includes: Collecting soil information of the current sowing area, the soil information includes: soil temperature, soil moisture and soil density; Determine target soil information required for target sowing seeds according to the seed type, wherein the target soil information includes: optimal soil temperature, optimal soil moisture and optimal soil density; Based on the soil information and the target soil information, determining the planting attribute values ​​of the target sowing seeds at different soil depths in the current sowing area through a planting attribute value calculation formula, wherein the planting attribute values ​​are used to characterize the suitability of the target sowing seeds for planting at each soil depth; Determining the optimal planting depth of the target sowing seed in the current sowing area based on the planting attribute value; The calculation formula of the planting attribute value is: Planting attribute value = {(soil temperature - optimal soil temperature) 2 + (soil moisture – optimum soil moisture) 2 + (soil density*10 -7 -Optimal soil density*10 -7 ) 2 } / 3; The step of laying the seed carrier material to the front sowing area by the sowing equipment based on the optimal planting spacing and the number of sowing rows in the area to plant the target sowing seeds includes: The seed carrier material is spread to the front sowing area by sowing equipment based on the optimal planting spacing, the number of sowing rows in the area and the optimal planting depth to plant the target sowing seeds.

2. The method according to claim 1, characterized in that The step of determining the seed type and seed maturity of the seeds to be sown according to the seed image of the seeds to be sown comprises: Extracting shape features and color features of the seeds to be sown from the seed images of the seeds to be sown; Obtaining the standard shape features corresponding to each template seed through the standard seed images corresponding to several template seeds; Determine a target template seed that matches the seed to be sown based on the shape feature and the standard shape feature, and determine a target seed type of the target template seed as the seed type of the seed to be sown; Searching for all seed color images corresponding to the target seed type, wherein the seed color image is used to characterize the maturity of the target template seed; The seed maturity of the seeds to be sown is determined based on the color feature and the seed color image.

3. The method according to claim 2, characterized in that The step of determining the seed maturity of the seeds to be sown based on the color feature and the seed color image comprises: Obtaining the standard color features corresponding to the target template seed at different maturity levels through the seed color image; Determining a similarity between the color feature and the standard color feature; Determining a target color feature that matches the color feature from the standard color features based on the similarity; The seed maturity of the seeds to be sown is determined based on the target color characteristics.

4. The method according to any one of claims 1 to 3, characterized in that After the step of laying the seed carrier material to the front sowing area by the sowing equipment based on the optimal planting spacing, the number of sowing rows in the area and the optimal planting depth to plant the target sowing seeds, the method further includes: During the laying process, obtaining obstacle information around the sowing equipment in real time; Determine a target planting position of the target sowing seeds in the current sowing area; generating an obstacle map of the current sowing area based on the obstacle information and the target planting position; Generate a sowing driving path corresponding to the sowing equipment based on the obstacle map and the target planting position; The seed carrier material is laid to the front sowing area by the sowing equipment based on the sowing travel path, the optimal planting spacing, the number of sowing rows in the area and the optimal planting depth to plant the target sowing seeds.

5. The method according to claim 4, characterized in that The step of generating an obstacle map of the current sowing area based on the obstacle information and the target planting position comprises: Determine all obstacles in the current sowing area according to the obstacle information; Determining the obstacle probability corresponding to each obstacle object based on the target planting position; An obstacle map of the current sowing area is generated based on the obstacle probability.

6. An intelligent seeding device, characterized in that: The device comprises: A seed information determination module, used to determine the seed type and seed maturity of the seeds to be sown according to the seed image of the seeds to be sown; A planting strategy determination module, used to determine a target sowing seed from the seeds to be sown based on the seed type and the seed maturity, and a target planting strategy corresponding to the target sowing seed; A sowing information determination module, used to determine the optimal planting spacing of the target sowing seeds and the number of regional sowing rows according to the target planting strategy; A seed bonding module, used for bonding the target sowing seeds to a seed carrier material through a seed bonding and rolling process; A seed planting module, used for laying the seed carrier material to the front sowing area based on the optimal planting spacing and the number of sowing rows in the area through a sowing device, so as to plant the target sowing seeds; The seed planting module is also used to collect soil information of the current sowing area, and the soil information includes: soil temperature, soil moisture and soil density; determine the target soil information required for the target sowing seed according to the seed type, and the target soil information includes: optimal soil temperature, optimal soil moisture and optimal soil density; based on the soil information and the target soil information, determine the planting attribute value of the target sowing seed at different soil depths in the current sowing area through a planting attribute value calculation formula, and the planting attribute value is used to characterize the suitability of the target sowing seed to be planted at each soil depth; determine the optimal planting depth of the target sowing seed in the current sowing area based on the planting attribute value; wherein the planting attribute value calculation formula is: planting attribute value={(soil temperature-optimal soil temperature) 2 + (soil moisture – optimum soil moisture) 2 + (soil density*10 -7 - Optimal soil density*10 -7 ) 2 } / 3; The seed carrier material is spread to the front sowing area through sowing equipment based on the optimal planting spacing, the number of sowing rows in the area and the optimal planting depth to plant the target sowing seeds.

7. An intelligent sowing device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the intelligent seeding method according to any one of claims 1 to 5.

8. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the intelligent seeding method according to any one of claims 1 to 5 are implemented.

9. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the intelligent sowing method according to any one of claims 1 to 5 are implemented.

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