Description:BACKGROUND
Field of Invention
[001] Embodiments of the present invention generally relate to a monitoring platform and particularly to a soil nutrient and crop yield recommendation platform.
Description of Related Art
[002] Monitoring nutrient levels in the soil is crucial to maintain a balanced nutrition profile and maximize crop yields. Nutrient monitoring sensors facilitate precise measurement of essential nutrients, encompassing both macronutrients and micronutrients. Continuous monitoring of these nutrient levels enables farmers to adjust pesticide practices, ensuring plants receive adequate nutrition for optimal growth and development. Micronutrient monitoring minimizes the risk of nutrient deficiencies or excesses, ultimately enhancing crop quality and reducing environmental impact.
[003] Additionally, traditional soil monitoring methods often involve laborious and time-consuming procedures, such as manual sampling and laboratory analysis, resulting in delayed results and a lack of real-time monitoring capabilities. To address these challenges, automated soil nutrient and crop yield recommendation platforms have emerged, leveraging advanced technologies to provide precise and timely data on various soil parameters. A contemporary recommendation platform typically consists of a combination of hardware sensors, data collection devices, and software analytics tools, working synergistically to measure, collect, analyze, and visualize data related to diverse soil properties and characteristics.
[004] Nonetheless, several smart and remotely controlled solutions exist that can sense soil fertility and nutrient requirements. These systems often remain cost-prohibitive for farmers and present challenges regarding installation and usability.
[005] There is thus a need for an improved and advanced method for generating customized pesticide recommendations that can administer the abovementioned limitations in a more efficient manner.
SUMMARY
[006] Embodiments in accordance with the present invention provide a soil nutrient and crop yield recommendation platform. The soil nutrient and crop yield recommendation platform comprising: a nutrient sensor configured to sense nutrient levels of a soil sample; an imaging unit configured to capture crop images in real time; and a transmitter connected to the nutrient sensor and the imaging unit. The transmitter is configured to receive sensor data from the nutrient sensor, and the captured crop images from the imaging unit; and a processing unit connected to the transmitter, and configured to: receive the sensor data and the captured crop images from the transmitter; enabling the processing unit to analyze the received sensor data to evaluate an amount of macronutrients, and the captured crop images using a machine learning algorithm; determine a crop yield based on the evaluated amounts of macronutrients, and the analyzed crop images; and generate customized pesticide recommendations based on the determined crop yield.
[007] Embodiments in accordance with the present invention further provide a method for generating customized pesticide recommendations using a soil nutrient and crop yield recommendation platform, the method comprising steps of: sensing nutrient levels of a soil sample using a nutrient sensor; capturing crop images in real-time using an imaging unit; receiving sensor data from the nutrient sensor and the captured crop images from the imaging unit using a transmitter; transmitting the received sensor data, and the captured crop images to a processing unit; analyzing the received sensor data to evaluate an amount of macronutrients, and the captured crop images using the processing unit; determining a crop yield by comparing the evaluated amounts of macronutrients, and the analyzed crop images; and generating customized pesticide recommendations based on the determined crop yield.
[008] Embodiments of the present invention may provide several advantages depending on configuration. First, embodiments of the present application may provide a soil nutrient and crop yield recommendation platform.
[009] Next, embodiments of the present application may provide a soil nutrient and crop yield recommendation platform that is easy to use and install.
[0010] Next, embodiments of the present application may provide a soil nutrient and crop yield recommendation platform that improves a soil fertility and plant health.
[0011] Next, embodiments of the present application may provide a soil nutrient and crop yield recommendation platform that operates on a domestic and academic research level.
[0012] Next, embodiments of the present application may provide a soil nutrient and crop yield recommendation platform that bears low maintenance costs.
[0013] Next, embodiments of the present application may provide a soil nutrient and crop yield recommendation platform that is workable and sustainable for a longer period of time.
[0014] These and other advantages will be apparent from the present application of the embodiments described herein.
[0015] The preceding is a simplified summary to provide an understanding of some embodiments of the present invention. This summary is neither an extensive nor exhaustive overview of the present invention and its various embodiments. The summary presents selected concepts of the embodiments of the present invention in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other embodiments of the present invention are possible by utilizing, alone or in combination, one or more of the features set forth above or described in detail below.
BRIEF DESCRIPTION OF THE DRAWINGS
[0016] The above and still further features and advantages of embodiments of the present invention will become apparent upon consideration of the following detailed description of embodiments thereof, especially when taken in conjunction with the accompanying drawings, and wherein:
[0017] FIG. 1 illustrates a block diagram of a soil nutrient and crop yield recommendation platform, according to an embodiment of the present invention;
[0018] FIG. 2 illustrates a block diagram of a processing unit of the soil nutrient and crop yield recommendation platform, according to an embodiment of the present invention; and
[0019] FIG. 3 depicts a flowchart of a method for generating customized pesticide recommendations using a soil nutrient and crop yield recommendation platform.
[0020] The headings used herein are for organizational purposes only and are not meant to be used to limit the scope of the description or the claims. As used throughout this application, the word "may" is used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Similarly, the words “include”, “including”, and “includes” mean including but not limited to. To facilitate understanding, like reference numerals have been used, where possible, to designate like elements common to the figures. Optional portions of the figures may be illustrated using dashed or dotted lines, unless the context of usage indicates otherwise.
DETAILED DESCRIPTION
[0021] The following description includes the preferred best mode of one embodiment of the present invention. It will be clear from this description of the invention that the invention is not limited to these illustrated embodiments but that the invention also includes a variety of modifications and embodiments thereto. Therefore, the present description should be seen as illustrative and not limiting. While the invention is susceptible to various modifications and alternative constructions, it should be understood, that there is no intention to limit the invention to the specific form disclosed, but, on the contrary, the invention is to cover all modifications, alternative constructions, and equivalents falling within the scope of the invention as defined in the claims.
[0022] In any embodiment described herein, the open-ended terms "comprising", "comprises”, and the like (which are synonymous with "including", "having” and "characterized by") may be replaced by the respective partially closed phrases "consisting essentially of", “consists essentially of", and the like or the respective closed phrases "consisting of", "consists of”, the like.
[0023] As used herein, the singular forms “a”, “an”, and “the” designate both the singular and the plural, unless expressly stated to designate the singular only.
[0024] FIG. 1 illustrates a block diagram of a soil nutrient and crop yield recommendation platform 100, (hereinafter referred to as the platform 100), according to an embodiment of the present invention. In an embodiment of the present invention, the platform 100 may check levels of macronutrients in soil. In an embodiment of the present invention, the platform 100 may monitor a temperature of the soil sample in real-time. The soil nutrient and crop yield recommendation platform 100, in an embodiment of the present invention, is configured to monitor the micronutrient levels, and the soil temperature together. By monitoring these parameters collectively, the platform 100 may offer several benefits. For instance, the platform 100 may enable a user to understand how pesticides influence a crop health. Pests and insects may result in nutrient leaching, where essential nutrients are washed away from a root zone. Thereby, the soil nutrient and crop yield recommendation platform 100 may facilitate an integrated approach to optimize plant growth, nutrient utilization, and overall soil fertility.
[0025] The soil nutrient and crop yield recommendation platform 100 may analyze the received sensor data. Further, the soil nutrient and crop yield recommendation platform 100 may determine crop yield by evaluating amounts of macronutrients. The soil nutrient and crop yield recommendation platform 100 may generate customized pesticide recommendations based on the crop yield. According to an embodiment of the present invention, the platform 100 may comprise a nutrient sensor 102, an imaging unit 104, a temperature sensor 106, a transmitter 108, a processing unit 110, and a mobile device 112.
[0026] In an embodiment of the present invention, the nutrient sensor 102 may be configured to sense the nutrient levels of the soil sample. In a preferred embodiment of the present invention, the nutrient sensor 102 may be a micronutrient sensor. In another embodiment of the present invention, the nutrient sensor 102 may be, but not limited to a Calcium/Magnesium Sensor, a Carbon/Nitrogen (C/N) Ratio Sensor, a conductivity measurement sensor, an electrochemical sensor, an optical sensor, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the nutrient sensor 102, including known, related art, and/or later developed technologies.
[0027] The nutrient sensor 102 may be inserted into the soil, which may further sense a presence of macronutrient levels, in an embodiment of the present invention. In an exemplary embodiment of the present invention, the micronutrient level of the soil may be high. In another exemplary embodiment of the present invention, the micronutrient level of the soil may be low. In another exemplary embodiment of the present invention, the micronutrient level of the soil may be moderate.
[0028] In an embodiment of the present invention, the imaging unit 104 may be configured to capture the crop images in real-time. The imaging unit 104 may be located at a pole (not shown) to capture crop images, in an embodiment of the present invention.
[0029] In an embodiment of the present invention, the temperature sensor 106 may be configured to monitor a temperature of the soil sample in real-time. According to embodiments of the present invention, the temperature sensor 106 may be, but not limited to, a thermistor sensor, a thermocouple sensor, a thermocouple wire sensor, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the temperature sensor 106, that may sense the temperature of the soil in real-time, including known, related art, and/or later developed technologies.
[0030] According to embodiments of the present invention, the temperature sensor 106 may be measured in magnitude of units such as, but not limited to, degree Celsius, a degree Fahrenheit, a degree Kelvin, and so forth. Embodiments of the present invention are intended to include or otherwise cover any magnitude of unit in which the temperature sensor 106 may sense the temperature of the soil, including known, related art, and/or later developed technologies.
[0031] In an embodiment of the present invention, the nutrient sensor 102, the imaging unit 104, and the temperature sensor 106 may be encapsulated together in a form of a sensor kit (not shown). The sensor kit may be dipped into the soil up to a predefined depth. According to embodiments of the present invention, the predefined depth may be in a range from 1 centimeter (cm) to 15 centimeters (cm). Embodiments of the present invention are intended to include or otherwise cover any range of depth.
[0032] In an embodiment of the present invention, the soil nutrient and crop yield recommendation platform 100 may have a power source (not shown). in an embodiment of the present invention, the power source may be connected to the transmitter 108. the power source may further supply operational power to the transmitter 108, in an embodiment of the present invention. In an embodiment of the present invention, the power supplied from the power source may be regulated using the regulator. In an exemplary embodiment of the present invention, the power source may provide power from a battery. In another exemplary embodiment of the present invention, the power source may provide power from a wall-outlet power supply. In yet another exemplary embodiment of the power source may supply power from any source.
[0033] In an embodiment of the present invention, the battery may be a rechargeable battery. In another embodiment of the present invention, the battery may be a non-rechargeable battery. According to embodiments of the present invention, the battery may be of any composition such as, but not limited to, a Nickel-Cadmium battery, a Nickel-Metal Hydride battery, a Zinc-Carbon battery, a Lithium-Ion battery, and so forth. Embodiments of the present invention are intended to include or otherwise cover any composition of the battery, that may provide a power source, including known, related art, and/or later developed technologies.
[0034] In an embodiment of the present invention, the wall-outlet power source may be from a grid power line source. In another embodiment of the present invention, the wall-outlet power source may be from a generator line power source. According to embodiments of the present invention, the wall-outlet power source may be of any rating such as, but not limited to, a 110-volt supply, a 220-volt supply, and so forth. Embodiments of the present invention are intended to include or otherwise cover any rating of the wall-outlet power source, including known, related art, and/or later developed technologies.
[0035] In an embodiment of the present invention, the transmitter 108 may be connected to the nutrient sensor 102, and the imaging unit 104. the transmitter 108 is configured to receive sensor data from the nutrient sensor 102, and the captured crop images from the imaging unit 104, in an embodiment of the present invention. the transmitter 108 may be configured to execute computer-executable instructions stored in the memory (not shown) to generate an output relating to the soil nutrient and crop yield recommendation platform 100. According to embodiments of the present invention, the memory may be, but not limited to, a Random-Access Memory (RAM), a Static Random-Access Memory (SRAM), a Dynamic Random-Access Memory (DRAM), a Read-Only Memory (ROM), an Erasable Programmable Read-only Memory (EPROM), a NAND Flash, a Secure Digital (SD) memory, a cache memory, a Hard Disk Drive (HDD), a Solid-State Drive (SSD), and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the memory, including known, related art, and/or later developed technologies.
[0036] According to embodiments of the present invention, the transmitter 108 may be, but not limited to, a Programmable Logic Control (PLC) unit, a microprocessor, a development board, and so forth. In a preferred embodiment of the present invention, the transmitter 108 may be an ESP32 transmitter. Embodiments of the present invention are intended to include or otherwise cover any type of the transmitter 108 including known, related art, and/or later developed technologies.
[0037] The transmitter 108 may generate and transmit customized pesticide recommendations based on the determined crop yield to the processing unit 110, in an embodiment of the present invention. In an embodiment of the present invention, the transmission from the transmitter 108 to the processing unit 110 may be wireless. In another embodiment of the present invention, the transmission from the transmitter 108 to the processing unit 110 may be wired. In an embodiment of the present invention, the processing unit 110 may receive sensor data collected by the transmitter 108. The processing unit 110 may analyze the received sensor data to evaluate the levels of macronutrients. Based on this analysis, the processing unit 110 may determine the crop yield and generate customized pesticide recommendations tailored to the specific crop yield.
[0038] According to embodiments of the present invention, the processing unit 110 may be, but not limited to a wired communication network, a wireless network, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the processing unit 110, including known, related art, and/or later developed technologies. In an embodiment of the present invention, components of the processing unit 110 may be explained in conjunction with FIG. 2.
[0039] According to embodiments of the present invention, the wired communication network may be enabled by means such as, but not limited to, a twisted pair cable, a co-axial cable, an Ethernet cable, a modem, a router, a switch, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the means that may enable the wired communication network, including known, related art, and/or later developed technologies.
[0040] According to embodiments of the present invention, the wireless network may be enabled by means such as, but not limited to, a Wi-Fi communication module, a Bluetooth communication module, a millimeter waves communication module, an Ultra-High Frequency (UHF) communication module, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the means that may enable the wireless network, including known, related art, and/or later developed technologies.
[0041] According to the embodiment of the present invention, a prototype of the soil nutrient and crop yield recommendation platform 100, may include the nutrient sensor 102, the imaging unit 104, and the temperature sensor 106 together dipped in soil. The processing unit 110 may be configured to transmit the generated customized pesticide recommendations to a mobile device 112, in an embodiment of the present invention. The user's mobile device 112, may be, but not limited to a tablet, a phone, a computer, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the mobile device 112, that may notify the user about the crop yield, including known, related art, and/or later developed technologies.
[0042] FIG. 2 illustrates a block diagram of the processing unit 110 of the soil nutrient and crop yield recommendation platform 100, according to an embodiment of the present invention. The processing unit 110 may comprise a data receiving module 200, a data analyzing module 202, a condition determination module 204, and a recommendation module 206.
[0043] According to an embodiment of the present invention, the data receiving module 200 may be configured to receive the collected sensed data from the nutrient sensor 102, and the imaging unit 104 from the transmitter 108. Further, the data receiving module 200 may be configured to transmit the received sensed amounts of macronutrients to the processing unit 110 to activate data analyzing module 202, in an embodiment of the present invention.
[0044] In an embodiment of the present invention, the data analyzing module 202 may be configured to analyze the collected sensed data from the nutrient sensor 102 and the imaging unit 104 using a machine learning algorithm. The machine learning algorithm may be a random forest algorithm. Further, the data analyzing module 202 may be configured to transmit the analyzed amounts of macronutrients to the condition determination module 204, in an embodiment of the present invention. The analyzed amounts of macronutrients may be compared with respective threshold values that may be pre-stored in a memory. These prestored threshold values may serve as references for determining whether the crop yield meets a desired criterion. Further, by comparing the analyzed amounts of macronutrients with the prestored threshold values, the data analyzing module 202 may enable the condition determination module 204 to provide a quantitative assessment of the crop yield.
[0045] According to the embodiment of the present invention, the condition determination module 204 may determine the crop yield by evaluating amounts of macronutrients from nutrient sensor 102 and imaging unit 104. Further, the soil condition determination module 204 activates the recommendation module 206 in an embodiment of the present invention. In an embodiment of the present invention, upon receiving the analyzed amounts of macronutrients, the recommendation module 206, may generate customized pesticide recommendations based on the crop yield.
[0046] The recommendation module 206 may incorporate an artificial intelligence (AI) driven optimization algorithm that may continuously learn from the collected data and adapt the pesticide recommendations over time. This unique feature allows the soil nutrient and crop yield recommendation platform 100 to dynamically adjust the pesticide prescriptions based on evolving crop yield, crop growth stages, and environmental factors, maximizing the efficiency and effectiveness of nutrient management. In an embodiment of the present invention, the AI driven optimization algorithm may be trained using data, that may be but not limited to, the sensor data, a historical crop performance data, and external environmental factors to identify patterns, correlations, and trends. The AI driven optimization algorithm may use the training data to fine-tune the pesticide recommendations based on the evolving crop yield, crop growth stages, and environmental factors. The AI algorithm may compare the real-time sensor data with a historical data to detect anomalies, and the recommendation module 206 may trigger alerts or notifications to the farmer when significant deviations are identified.
[0047] In an embodiment of the present invention, the generated pesticide recommendations may be, but not limited, a required pesticide proportion, application rates, a weather suggestion, a timing suggestion for applying pesticide, and so forth. Embodiments of the present invention are intended to include or otherwise cover any recommendation, including known, related art, and/or later developed technologies.
[0048] FIG. 3 depicts a flowchart of a method 300 for generating the customized pesticide recommendations using a soil nutrient and crop yield recommendation platform 100, in an embodiment of the present invention.
[0049] at step 302, the soil nutrient and crop yield recommendation platform 100 may sense the nutrient levels of a soil sample using a nutrient sensor 102.
[0050] At step 304, the soil nutrient and crop yield recommendation platform 100 may capture the crop images from the imaging unit 104.
[0051] At step 306, the transmitter 108 may receive the sensor data from the nutrient sensor 102 and the captured crop images from the imaging unit 104.
[0052] At step 308, the transmitter 108 may transmit the received sensor data to the processing unit 110.
[0053] At step 310, the processing unit 110 may analyze the received sensor data for evaluating amounts of macronutrients, and the captured crop images using the processing unit 110.
[0054] At step 312, the processing unit 110 may determine crop yield by comparing the evaluated amounts of macronutrients, and the analyzed crop images.
[0055] At step 314, the processing unit 110 may generate and transmit the customized pesticide recommendations based on the specific crop yield to the mobile device 112.
[0056] While the invention has been described in connection with what is presently considered to be the most practical and various embodiments, it is to be understood that the invention is not to be limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims.
[0057] This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the invention is defined in the claims and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements within substantial differences from the literal languages of the claims. , Claims:CLAIMS
I/We Claim:
1. A soil nutrient and crop yield recommendation platform (100) comprising:
a nutrient sensor (102) configured to sense nutrient levels of a soil sample;
an imaging unit (104) configured to capture crop images in real-time;
a transmitter (108) connected to the nutrient sensor (102) and the imaging unit (104), characterized in that the transmitter (108) is configured to receive sensor data from the nutrient sensor (102), and the captured crop images from the imaging unit (104); and
a processing unit (110) connected to the transmitter (108), and configured to:
receive the sensor data and the captured crop images from the transmitter (108);
enable the processing unit (110) to analyze the received sensor data to evaluate an amount of macronutrients, and the captured crop images using a machine learning algorithm;
determine a crop yield based on the evaluated amounts of macronutrients, and the analyzed crop images; and
generate customized pesticide recommendations based on the determined crop yield.
2. The platform (100) as claimed in claim 1, wherein the machine learning algorithm is a random forest algorithm.
3. The platform (100) as claimed in claim 1, wherein the pesticide recommendations are selected from required pesticide proportions, application rates, weather suggestions, and timing suggestions for applying pesticide, or a combination thereof.
4. The platform (100) as claimed in claim 1, wherein the transmitter (108) wirelessly transmits the received sensor data to the processing unit (110).
5. The platform (100) as claimed in claim 1, wherein the transmitter (108) is an ESP32 transmitter.
6. The platform (100) as claimed in claim 1, wherein the processing unit (110) is configured to transmit the generated customized pesticide recommendations to a mobile device (112).
7. A method for generating customized pesticide recommendations using a soil nutrient and crop yield recommendation platform (100), the method comprising steps of:
sensing nutrient levels of a soil sample using a nutrient sensor (102);
capturing crop images in real-time using an imaging unit (104);
receiving sensor data from the nutrient sensor (102) and the captured crop images from the imaging unit (104) using a transmitter (108);
transmitting the received sensor data, and the captured crop images to a processing unit (110);
analyzing the received sensor data to evaluate an amount of macronutrients, and the captured crop images using the processing unit (110);
determining a crop yield by comparing the evaluated amounts of macronutrients, and the analyzed crop images; and
generating customized pesticide recommendations based on the determined crop yield.
8. The method as claimed in claim 7, comprising a step of monitoring temperature of the soil sample in real-time using a temperature sensor (106).
9. The method as claimed in claim 7, comprising a step of transmitting the generated customized pesticide recommendations from the processing unit (110) to a mobile device (112).
10. The method as claimed in claim 7, wherein the pesticide recommendations are selected from required pesticide proportions, application rates, weather suggestions, and timing suggestions for applying pesticide, or a combination thereof.

Date: November 29, 2023
Place: Noida

Dr. Keerti Gupta
Agent for the Applicant
(IN/PA-1529)