Description:FIELD OF THE INVENTION

[0001] The present invention relates to a crop health monitoring and remediation device that is capable of automatically analyzing crop health by assessing the condition of crop leaves, detecting potential diseases, and enabling precise navigation across farm field to ensure targeted inspection and treatment based on user input and real-time field conditions.

BACKGROUND OF THE INVENTION

[0002] Crop health monitoring is essential for ensuring sustainable agriculture and maximizing yields. As climate change, pests, diseases, and soil degradation threaten crop production, timely identification of these factors is crucial. Regular monitoring helps detect early signs of stress, nutrient deficiencies, pest infestations, or disease outbreaks, which drastically reduce crop productivity if left unaddressed. By leveraging technologies such as satellite imaging, drones, and sensors, farmers gain real-time insights into the health of their crops, enabling targeted interventions rather than broad, indiscriminate treatments. This approach reduces the use of harmful chemicals, minimizes environmental impact, and saves costs. Remediation measures, such as adjusting irrigation, applying targeted fertilizers, or using biocontrol agents, be implemented quickly to address identified issues, improving overall crop resilience. Additionally, data-driven insights allow for precise decision-making and better resource allocation, optimizing farm operations. In an era of global food security challenges, crop health monitoring and remediation are indispensable for maintaining healthy crops, ensuring sustainable farming practices, and enhancing food production efficiency to meet the growing demands of the population.

[0003] Traditional methods of crop health monitoring often rely on visual inspections, manual field surveys, and farmer experience to detect signs of stress, pests, or diseases. Farmers may walk through their fields, looking for visible symptoms such as wilting, discoloration, or pest damage, and sometimes use basic tools like soil probes to check moisture levels. Remediation typically involves blanket treatments such as spraying pesticides or applying fertilizers without precise targeting, which lead to inefficiencies. These methods are time-consuming, labor-intensive, and limited by the farmer’s ability to cover large areas in a timely manner. They also depend on subjective judgment, making it difficult to detect early signs of issues before they spread. Additionally, the broad application of chemicals often results in overuse, which harm the environment, degrade soil quality, and create resistance in pests or pathogens. Traditional methods also lack the ability to provide real-time, data-driven insights, limiting their effectiveness in dynamic conditions. These drawbacks make it harder to manage crop health efficiently, leading to increased costs, reduced yields, and potential long-term environmental damage. As a result, there is a growing need for more precise, technology-driven approaches to monitoring and remediation.

[0004] US20170032258A1 discloses about an invention that has a system and methods for monitoring and assessing crop health and performance can provide rapid screening of individual plants. The devices and methods have an automated component, and rely primarily on the detection and interpretation of plant-based signals to provide information about crop health. In some cases knowledge from human experts is captured and integrated into the automated crop monitoring devices and methods. Predictive models can also be developed and used to predict future health of plants in a crop.

[0005] US20170030877A1 discloses about an invention that has a multi-sensor device comprises a housing containing multiple sensor modules for capturing and transmitting sensor data for plants in a crop. A control unit within the housing is operable to control the sensor modules, and a communications interface is connected to the control unit for transmitting data from said plurality of sensor modules. The sensor modules can include a physiological sensor, a surface analysis sensor, and chemical sensor. The multi-sensor device can be used as a hand-held device or mounted to a mobile platform for use in an automated crop monitoring device.

[0006] Conventionally, many methods are available for carrying out monitoring of crops. However, the cited invention lacks in fall short in terms of scalability, efficiency, and real-time accuracy. Many existing methods require significant human intervention for data interpretation and decision-making, which lead to delays in identifying and addressing crop health issues. Consequently, there is a need for more sophisticated and fully automated solutions that provide real-time, accurate crop monitoring, disease detection, and customized treatment recommendations, all with minimal human involvement and maximum efficiency.

[0007] In order to overcome the aforementioned drawbacks, there exists a need in the art to develop a device that is capable of providing fully automated, real-time monitoring and diagnosis of crop health, enabling precise detection of diseases and deficiencies across large areas with minimal human intervention. The device should be able to analyze various crop health indicators, such as the condition of leaves, soil, and overall plant status.

OBJECTS OF THE INVENTION

[0008] The principal object of the present invention is to overcome the disadvantages of the prior art.

[0009] An object of the present invention is to develop a device that is capable of monitoring and diagnosing crop health by analyzing the condition of crop leaves and identifying potential diseases in real-time.

[0010] Another object of the present invention is to develop a device that is capable of enabling precise navigation of the device over farm fields, ensuring targeted and efficient inspection and treatment of specific areas based on user input and field conditions

[0011] Another object of the present invention is to develop a device that is capable of analyzing visual data to detect disease patterns on crop leaves and provide accurate disease identification and treatment recommendations.

[0012] Another object of the present invention is to develop a device that is capable of facilitating soil health assessment by incorporating a soil analysis, enabling the evaluation of soil conditions in relation to crop health and optimizing treatment strategies accordingly.

[0013] Another object of the present invention is to develop a device that is capable of storing and accessing a comprehensive database of disease management, thus allowing for customized treatments based on the type of disease detected and the crop’s health status.

[0014] Another object of the present invention is to develop a device that is capable of offering visual insights into disease spread, treatment effectiveness, and projected crop yields, assisting in better decision-making for optimized farm management.

[0015] Yet another object of the present invention is to develop a device that is capable of detecting color and moisture changes in leaves and stored samples, ensuring accurate diagnosis and ideal conditions for further analysis or treatment.

[0016] The foregoing and other objects, features, and advantages of the present invention will become readily apparent upon further review of the following detailed description of the preferred embodiment as illustrated in the accompanying drawings.

SUMMARY OF THE INVENTION

[0017] The present invention relates to a crop health monitoring and remediation device that analyze visual data, detect disease patterns on crop leaves, and offer accurate disease identification along with tailored treatment recommendations and soil health assessment with disease management strategies to optimize treatment application, ensuring efficient use of resources and effective crop care.

[0018] According to an embodiment of the present invention, a crop health monitoring and remediation device, comprising a housing positioned on a farm field, supported by track wheels for mobility, and a touch interactive display panel for user input. The device’s microcontroller processes the input and, using a GPS module, directs the housing to specified areas on the field. An artificial intelligence-based imaging unit, mounted on a robotic arm, captures and processes images of crop leaves to identify diseases, while a database stores disease management strategies. A soil sensor, integrated into an extendable gripper, assesses soil health, and the microcontroller uses the data to determine the appropriate treatment. The device also includes a storage chamber for chemicals, nutrients, and growth regulators, which are dispensed by an electronically controlled nozzle onto affected leaves based on the microcontroller’s analysis. Additionally, the device incorporates a color sensor for precise disease diagnosis, a four-bar linkage mechanism for removing infected leaves, and a moisture sensor in a container to preserve leaf samples for further analysis. An augmented reality (AR) projector provides real-time projections of disease spread, treatment effectiveness, and crop yield predictions, helping farmers make informed decisions. A battery powers all electronic components, ensuring continuous operation.

[0019] While the invention has been described and shown with particular reference to the preferred embodiment, it will be apparent that variations might be possible that would fall within the scope of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS

[0020] These and other features, aspects, and advantages of the present invention will become better understood with regard to the following description, appended claims, and accompanying drawings where:
Figure 1 illustrates an isometric view of a crop health monitoring and remediation device.

DETAILED DESCRIPTION OF THE INVENTION

[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 spirit and 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] The present invention relates to a crop health monitoring and remediation device provide farmers with real-time visual insights into disease spread, treatment effectiveness, and projected crop yields, aiding in better decision-making and optimized farm management which aids in detecting color and moisture changes in leaves and stored samples for precise diagnosis and ideal storage conditions for further analysis.

[0025] Referring to Figure 1, an isometric view of a crop health monitoring and remediation device is illustrated, comprising of a housing 101 positioned on ground surface, plurality of tracks wheels 102 arranged underneath the housing 101, a touch interactive display panel 103 mounted on the housing 101, an artificial intelligence-based imaging unit 104 mounted on the housing 101 via a robotic arm 105, an extendable gripper 106 for positioning a soil sensor 107 embedded in the gripper 106, a four-bar linkage arrangement 108 is integrated in between the housing 101 and gripper 106, a plucker 109 attached with the arrangement 108, a container 110 arranged in the housing 101, a storage chamber 111 arranged on the housing 101, a robotic link 112 attached with each of the section, an augmented reality (AR) LED holographic projector 113 mounted on upper section of the housing 101 and an electronically controlled nozzle 114 installed at end of link 112.

[0026] The device disclosed herein includes a housing 101 developed to be positioned on the ground surface of a farm field, ensuring that the device move efficiently and effectively across the terrain. This housing 101 acts as the central structure that houses all the essential components for providing both the physical support and the functional integration for the device. The housing 101 is constructed from durable materials, designed to withstand the environmental conditions typically found on agricultural fields, including exposure to dust, moisture, and various weather conditions. This is engineered to be robust and lightweight, offering a balance between strength and ease of mobility.

[0027] The housing 101 is equipped with a plurality of track wheels 102 arranged underneath it, which play a crucial role in enabling the device to move across the uneven and sometimes challenging surfaces of a farm field. These track wheels 102 are often favored in agricultural applications because they provide better stability and traction compared to traditional wheels. This design ensures that the device traverse through fields that have soft, muddy, or uneven ground surfaces, which are commonly encountered in farming environments. The tracks distribute the weight of the housing 101 more evenly across the surface, reducing the risk of the device getting stuck or causing damage to the field.

[0028] The track wheels 102 are typically developed with a rugged, all-terrain tread pattern that allows for optimal grip on various soil types, including loose or compacted soil, making the device highly adaptable to different farming conditions. They are also designed to absorb shocks and vibrations, ensuring that the device remains stable and functional while in motion, even on rough or uneven ground. The track wheels 102 are powered by a motor, controlled by the device’s microcontroller, allowing for precise navigation across the farm field. The motion of the housing 101 is adjusted, enabling the device to move forward, backward, or even pivot on the spot for optimal positioning in relation to the crop rows. The tracks are designed to ensure smooth movement across the field while minimizing the potential for soil compaction, which occur when heavy machinery is used.

[0029] A touch interactive display panel 103 is mounted on the housing 101 that serves as the primary interface for the user to interact with the device. This panel 103 allows the farmer or user to input specifications, access vital information, and control the device’s various functionalities related to crop health monitoring and treatment. Positioned conveniently on the housing 101, the display panel 103 is developed to be user-friendly, enabling intuitive navigation through its various options. The touch interface ensures that the user easily access detailed information about the condition of the crops, particularly the health of the leaves, which are often the first indicators of potential diseases or nutrient deficiencies in plants.

[0030] The display panel 103 provides a clear and interactive interface, where the user input specific parameters such as the type of crops being grown, the desired treatment options, and any particular concerns regarding plant health. The device is developed to give real-time access to various data points, including detailed images of crop leaves, soil conditions, and data about the current status of crop health across different sections of the field. The information displayed include, but is not limited to, the presence of pests, diseases, nutrient deficiencies, and other environmental stress factors affecting the crop.

[0031] The touch panel 103 is not only a data display tool but also allows the user to provide specific input commands to the device. These commands are processed by the microcontroller, interpreting the user’s requests and translating them into actionable operations. For example, if a user selects a specific crop section that needs attention, the microcontroller processes this input and directs the device to navigate to that section of the field. This navigation is synchronized with the Global Positioning System (GPS) module embedded within the device. The GPS module allows the device to accurately determine its location on the field and ensure that it moves precisely to the designated area based on the user’s specifications.

[0032] The microcontroller communicates with the motorized wheels 102 of the housing 101, activating them to move the housing 101 accordingly. It adjusts the speed and direction of the track wheels 102, enabling the housing 101 to navigate the farm field autonomously. The microcontroller also ensures that the movement is accurate and efficient by taking into account the terrain, obstacles, and specific areas requiring attention. The GPS module provides continuous updates on the housing’s position, allowing the microcontroller to keep track of its location in real-time, ensuring that the housing 101 reaches the exact points specified by the user for crop monitoring or treatment application. Furthermore, the housing 101 is designed to allow the user to define treatment parameters for the crop, such as the type of disease detected on the leaves, the required chemical or nutrient application, and the amount of treatment needed. Once the user inputs these details, the microcontroller links this information to the corresponding database, which contains disease management strategies.

[0033] An artificial intelligence (AI)-based imaging unit 104 mounted on the housing 101 for diagnosis of crop health, specifically targeting the condition of crop leaves. This imaging unit 104 is designed to detect, identify, and analyze a variety of issues that affect the leaves of crops, such as diseases, pests, or nutrient deficiencies. The imaging unit 104 is securely mounted on a robotic arm 105, which provides flexibility and precision in positioning the camera over the crop leaves. This robotic arm 105 is controlled by the microcontroller, which processes the inputs from the user or the automated device, ensuring the imaging unit 104 is placed in the optimal position to capture detailed images of the leaves.

[0034] The imaging unit 104 utilizes a combination of high-resolution cameras, sensors, and AI protocol to capture and process multiple images of the crop leaves from various angles. These images are then analyzed by a processor embedded in the unit. The processor works in tandem with the AI protocol to interpret the captured images, identifying key features and patterns that indicate the presence of pests, diseases, or other abnormalities affecting the crop. The AI imaging unit 104 is capable of detecting minute details, such as discolorations, lesions, spots, wilting, and other symptoms that are often early indicators of plant diseases.

[0035] The imaging unit 104 leverages machine learning techniques to continuously improve its ability to identify different types of leaves and diagnose diseases with increasing accuracy over time. By training the AI model on a large dataset of plant images with known disease patterns, the imaging unit 104 recognize specific diseases based on visual cues. For example, the AI differentiate between fungal infections, bacterial diseases, viral pathogens, or nutrient deficiencies, each of which may exhibit distinctive color changes, texture modifications, or growth patterns on the leaves. This ability to automatically classify and diagnose crop diseases without requiring manual intervention is a significant advancement in precision agriculture, enabling faster and more reliable identification of crop health issues.

[0036] In addition to the AI-based imaging unit 104, a color sensor is embedded in the housing 101, working in close synchronization with the imaging unit 104. The color sensor detects subtle changes in the color of the leaves, which is crucial for identifying early disease symptoms that are not visible to the naked eye. Plants often exhibit color changes when infected by pathogens; for instance, leaves turn yellow or exhibit dark spots as a result of nutrient deficiencies or fungal infections. By capturing these color changes, the sensor enhances the device's diagnostic capability, allowing it to detect specific diseases more accurately. The color sensor, along with the imaging unit 104, is particularly effective in identifying diseases that are associated with distinct color or structural patterns. For instance, diseases like powdery mildew or downy mildew often result in noticeable color changes on the surface of the leaves, such as the appearance of white or yellowish patches. Similarly, certain pests may leave behind damage that alters the color or structure of the leaf tissue. By analyzing these color variations in combination with the detailed imaging data, the device is able to provide a comprehensive diagnosis of the plant’s health.

[0037] As the robotic arm 105 moves the imaging unit 104 over different sections of the field, it captures images of the leaves in various locations, and the processor instantly analyzes these images, sending feedback to the microcontroller for further action. The imaging unit 104 even identifies clusters of affected plants, enabling targeted treatment, thus preventing the spread of disease or pest infestations to healthy plants.

[0038] By pairing AI-based image recognition with real-time data processing and color detection, this imaging unit 104 is able to offer a level of precision and efficiency in crop health monitoring that is unparalleled in traditional farming methods. The combination of high-quality imaging, AI-powered analysis, and color sensor allows for a comprehensive and accurate diagnosis of plant health, helping farmers identify issues early and take the necessary steps to treat or remediate problems before they escalate.

[0039] A database linked with the microcontroller that stores a vast array of information related to various disease management strategies, treatments, and best agricultural practices. This database is specifically designed to store detailed data on different types of diseases that affect crops, with a focus on the symptoms, causes, and recommended interventions for each disease. These strategies are not only disease-specific but are also tailored to the type of crop and its specific growth conditions. The microcontroller interfaces directly with this database, allowing the device to quickly retrieve the most appropriate disease management protocols when a specific condition is detected on the crop leaves.

[0040] When the artificial intelligence-based imaging unit 104 diagnoses a disease or other health-related issue on a crop leaf, the microcontroller queries the database to fetch the relevant disease management strategy associated with that particular condition. The database includes a range of possible treatments based on the type of disease and the crop’s needs. These strategies might include recommendations for pesticide applications, fungicides, bactericides, growth regulators, or other remedial actions, as well as detailed instructions on how to apply these treatments effectively to minimize crop damage while ensuring optimal growth. Additionally, the database includes information on the dosage, frequency, and timing of application, based on various environmental factors such as soil conditions, climate, and stage of crop development.

[0041] The data stored in the database is constantly updated, ensuring that it incorporates the latest research, pest and disease management strategies, and recommendations. The microcontroller ensures that the disease management strategies are relevant to the crop type being monitored, as well as the specific symptoms that have been detected. For example, if the device identifies a fungal infection on the leaves of a tomato plant, the database recommends a particular fungicide along with specific instructions for its application, including the amount to be applied, the areas to treat, and the required frequency of treatment. The ability to access such a well-structured and comprehensive database allows the device to deliver precision treatments that are tailored to the specific needs of the crop, improving overall crop health and reducing the likelihood of over-application of harmful chemicals.

[0042] In addition to managing disease-related data, the device also monitors the overall health of the soil, which is integral to the successful growth and health of crops. To assess soil health, the device is equipped with an extendable gripper 106 that holds a soil sensor 107. This gripper 106 is actuated by the microcontroller and extend or retract to position the soil sensor 107 in the ground at a specified depth. The gripper 106 is designed to interact with the soil without damaging the surrounding crops, and it ensures that the sensor is placed at the optimal location for accurate readings. The soil sensor 107 embedded in the gripper 106 measures various key parameters, such as soil moisture, pH levels, temperature, and nutrient content.

[0043] Soil health plays a crucial role in the overall success of the crop, as it directly affects the availability of water and nutrients to the plant. If the soil is not healthy, even the most effective disease management strategies do not yield the desired results, as the plant do not have access to the necessary nutrients for growth. The soil sensor 107, by analyzing these critical parameters, provides real-time data on the soil’s condition, which is then processed by the microcontroller to assess whether any soil remediation is required. For example, if the sensor detects that the soil is too acidic or alkaline, or if there is a deficiency in a specific nutrient, the device retrieves relevant information from the database on how to remedy those conditions. This involve the application of soil amendments, fertilizers, or other treatments aimed at improving soil quality

[0044] The connection between the database and the soil sensor 107 enables the device to offer a more comprehensive approach to crop health management. In cases where the soil is determined to be unhealthy, the device recommend targeted interventions, such as adjusting pH levels, adding specific fertilizers, or improving drainage to enhance soil health. These recommendations, combined with the disease management strategies retrieved for the affected crop, allow the device to optimize the treatment for both the plant and the soil simultaneously. This integrated approach ensures that the crops receive the necessary care not just for their immediate disease symptoms but also for their overall growing conditions, leading to healthier, more productive plants in the long term

[0045] Ultimately, the combination of disease management strategies from the database and the real-time soil health analysis provided by the gripper 106-based sensor device makes the crop health monitoring and remediation device an incredibly powerful tool for precision agriculture. It enables farmers to take informed, targeted actions that improve both the plant’s health and the soil's fertility, resulting in higher yields, more sustainable farming practices, and a more efficient use of resources

[0046] A four-bar linkage arrangement 108 between the housing 101 and the gripper 106 is installed to facilitate the precise and controlled movement of a plucker 109. This plucker 109 is crucial for removing infected leaves from crops, an essential part of maintaining crop health and preventing the spread of disease. The four-bar linkage is a mechanical arrangement that consists of four rigid links connected by four rotational pairs, which allows for controlled movement and positioning of the plucker 109 in relation to the crop leaves. This linkage device enables the gripper 106 to extend and retract in a highly efficient manner, offering flexibility and precision in accessing different areas of the crop field.

[0047] The four-bar linkage primary function is to allow the plucker 109, attached to the gripper 106, to move with high accuracy, thereby ensuring that only the infected or diseased leaves are picked. The pucker’s design ensures this selectively target and remove leaves without damaging healthy plant parts. Once a disease is detected on a leaf by the artificial intelligence-based imaging unit 104, the device actuates the four-bar linkage mechanism. The linkage moves the gripper 106 to the exact position above the infected leaf, where the plucker 109 extend, gently grasp the leaf, and remove it from the plant. After the leaf is plucked, it is stored in a container 110 that is integrated into the housing 101.

[0048] The container 110 where the infected leaves are stored plays a crucial role in maintaining the disease’s characteristics for further analysis. Since these leaves are critical for diagnosing the disease, it is essential that they be stored in optimal conditions. A moisture sensor is embedded within this storage container 110 to monitor the moisture levels in real-time. The moisture sensor is a key component in ensuring that the leaves remain in a state that preserves their disease characteristics, which are necessary for further study and accurate identification. When leaves are removed from the plant, they begin to degrade or dry out quickly if not stored under proper conditions. This is where the moisture sensor comes into play, ensuring that the environment inside the container 110 remains humid enough to preserve the disease for further analysis

[0049] The moisture sensor continuously monitors the relative humidity inside the container 110 and sends this data back to the microcontroller, which processes it. If the moisture levels drop below the ideal threshold for storage, the device take corrective actions. For instance, the device trigger a small humidification device or alert the user to take manual action to add moisture, ensuring that the storage conditions are optimal for maintaining the leaf’s disease symptoms. This real-time monitoring prevents premature drying or degradation of the infected leaves, which hinder the diagnostic process and impact the quality of analysis.

[0050] A storage chamber 111 is integrated within the housing 101 and is designed to store these essential substances securely until they are needed for crop treatment. The materials stored in the chamber 111 are carefully selected to address a wide range of agricultural needs, including pest and disease control, soil enrichment, and plant growth promotion. The chamber 111 is divided into sections to hold different types of materials separately, preventing cross-contamination and ensuring that each material is stored under optimal conditions to maintain its effectiveness.

[0051] The microcontroller is vital in ensuring that the right amounts of chemicals, nutrients, and growth regulators are dispensed accurately for crop treatment. The microcontroller receives input data from various sources, including the disease management strategies fetched from the linked database, the soil health data from the soil sensor 107, and the specific needs of the crop based on its current condition and health status. It processes this information to determine the precise quantities of each material required for optimal treatment, taking into account factors such as the type of crop, the stage of its growth, and the presence of any diseases or pests

[0052] To achieve this, the microcontroller is connected to a machine learning protocol that analyzes the collected data and recommends the ideal chemicals or growth regulators to apply. For instance, the protocol suggests the use of copper sulfate or copper oxychloride to control fungal diseases, Bordeaux mixture for mildew, or sulfur-based products for controlling certain types of pests. The recommendations are based on historical data, disease symptoms detected on the crops, and soil health conditions, allowing the device to make informed and precise treatment recommendations. This ensures that the right chemical is applied in the right amount, minimizing the potential for overuse or misuse, which harm the crop or the environment.

[0053] Once the ideal treatment is determined, the microcontroller actuates a robotic link 112 attached to each section of the storage chamber 111. This robotic link 112 is responsible for extending or retracting the sections that hold the chemicals, nutrients, or growth regulators, allowing them to be positioned over the targeted crop areas where treatment is required. The robotic arm 105 is guided by the microcontroller, which uses GPS navigation to ensure precise location targeting. The arm 105 moves to the identified area where a disease or nutrient deficiency is present and carefully dispenses the required amount of material onto the affected area of the crop.

[0054] The robotic arm 105 ability to extend and retract allows for flexibility in targeting different parts of the crop field. For example, if the treatment is needed in a particular section of the field, the robotic arm 105 move directly over the affected leaves or soil. The device ensures that the chemicals or nutrients are applied precisely, avoiding waste and ensuring maximum effectiveness of the treatment. This is particularly important for managing diseases or pests, as localized treatment minimizes the spread of chemicals, reducing the environmental impact and ensuring that only the affected areas receive treatment. When the device identifies that the soil lacks specific nutrients, the robotic link 112 is activated to release the necessary growth regulators or fertilizers. The microcontroller takes into account soil health data from the sensors embedded in the housing 101, adjusting the amount of fertilizer or nutrient mix to suit the specific soil conditions, thereby optimizing crop growth.

[0055] An electronically controlled nozzle 114 installed at the end of the robotic link 112 plays a critical role in ensuring the effective and targeted application of chemicals, nutrients, and growth regulators onto the crop. This nozzle 114 is designed to be highly precise in its dispensing capabilities, enabling the device to apply the right amount of treatment to the affected areas of the crop or soil. By working in conjunction with the microcontroller and the robotic link 112, the nozzle 114 ensures that treatments are applied with high accuracy, minimizing waste and optimizing the benefits for the crop.

[0056] The nozzle 114 is electronically controlled, meaning that it is powered by the microcontroller, which directs its actions based on real-time inputs and pre-programmed treatment protocols. The nozzle’s electronic control is integral to maintaining consistency in the application process, ensuring that the correct volume and concentration of chemicals or nutrients are dispensed at the exact location where they are needed. This level of precision is critical in agricultural practices, where over-application or under-application of chemicals have adverse effects on the crop yield, environmental health, and overall farm economics.

[0057] When the device detects a disease, pest infestation, or nutrient deficiency in the crop, the microcontroller processes the information. Based on these inputs, the microcontroller calculates the ideal amount of chemical or nutrient needed for treatment. The treatment is a fungicide, pesticide, herbicide, or even a soil nutrient, depending on the crop’s needs and the detected problem. The microcontroller then activates the robotic arm 105, which extends and positions the nozzle 114 over the specific leaf or soil area that requires treatment

[0058] The nozzle's design is engineered for efficient chemical or nutrient dispersion. In the case of a chemical treatment, such as a pesticide or fungicide, the nozzle 114 is capable of atomizing the liquid into a fine mist or spray that is applied directly to the affected area of the leaf or plant. This ensures that the chemicals are distributed evenly and reach every part of the infected or stressed crop, providing targeted disease management. For nutrients or growth regulators, the nozzle 114 might operate differently, dispensing a liquid form of fertilizer or nutrient mixture directly onto the soil or plant base, enabling the crop to absorb the nutrients more effectively. This method allows the device to address localized deficiencies in soil or plant health without over-spreading fertilizers or chemicals to unaffected areas.

[0059] The nozzle's electronic control is particularly important when managing the application of growth regulators or soil supplements, as the correct amount and timing of nutrients is crucial for promoting optimal growth. Excessive use of fertilizers leads to nutrient imbalances, soil degradation, and even runoff, negatively impacting the environment. To avoid these issues, the nozzle 114 is integrated into the device’s overall control architecture, which ensures that nutrients are applied only when necessary and in the precise quantity needed for the crop’s recovery or growth. The robotic arm 105 also allows the nozzle 114 to be adjusted to different positions, ensuring it is directed to specific spots on the crop or field, based on the treatment requirements.

[0060] The nozzle 114 device works in tandem with the soil sensor 107, which is responsible for monitoring the soil's health and moisture levels. If the soil is found to be deficient in specific nutrients, the device uses the microcontroller to activate the appropriate nutrient section. The nozzle 114 is then directed over the soil, releasing a targeted amount of nutrients such as nitrogen, phosphorus, potassium, or trace minerals directly into the soil. This localized application of nutrients ensures that the crop's root device receives the necessary support to thrive, without wasteful overspreading of nutrients across the entire field. The nozzle 114 also plays a role in ensuring that treatment is delivered with minimal disruption to the environment. Since the device is highly localized and precision-driven, it reduces the amount of chemical runoff that might otherwise affect nearby plants, wildlife, or groundwater. This makes the entire treatment process more sustainable, lowering the environmental footprint of the crop management device

[0061] An augmented reality (AR) LED holographic projector 113 mounted on the upper section of the housing 101 for enhancing the user experience and enabling more informed decision-making in crop health management. This innovative feature utilizes cutting-edge technology to display real-time data and projections in a visual format, which overlaid directly onto the farmer’s field or onto a digital interface, enhancing both the understanding and management of crop health and treatment strategies.

[0062] The primary function of the AR projector 113 is to display critical information about the crop's health, such as the dispersion of diseases, the effectiveness of treatments applied, and predictions about the future crop yield based on current conditions and interventions. This real-time data is sourced from multiple sensors integrated into the device, including the imaging unit 104, soil sensor 107, and disease management databases. These sensors continuously monitor the condition of the crops, capturing data on leaf health, soil quality, pest infestations, and disease symptoms. The AR device processes this data and presents it in a user-friendly, interactive holographic format, allowing the user to see exactly where issues are located and how the crops are responding to treatment.

[0063] One of the most important applications of the AR projector 113 is for disease dispersion visualization. When a disease or pest is detected in the field, the AR projector 113 overlays a real-time map of disease spread directly on the field. This visualization shows the areas of the field that are most affected, as well as how the disease is spreading, based on factors such as wind patterns, moisture levels, and plant susceptibility. For example, if a fungal disease is detected, the AR display might highlight the areas where the fungus is most concentrated, with color-coded indicators showing the severity of infection in various sections of the crop. This immediate, visual feedback allows the farmer to act quickly and decisively, applying targeted treatments only where necessary, thus saving resources and optimizing treatment efficiency

[0064] The AR projector 113 is the treatment effectiveness display. After a treatment, such as a pesticide or nutrient application, the AR projector 113 shows how well the treatment is working, based on real-time data collected by the imaging unit 104 and sensors. For example, if a fungicide has been applied, the AR projector 113 show how the disease symptoms are diminishing over time or how the plant’s health is improving. The visual projections may include color changes, symptom reductions, or growth improvements in the affected areas, allowing the farmer to track the efficacy of the treatment at a glance. This feedback loop helps to ensure that farmers monitor the success of their interventions and make timely adjustments if necessary, for instance, by reapplying treatments or switching to alternative strategies if the current treatment is not proving effective.

[0065] In addition to providing real-time data about disease and treatment effectiveness, the AR projector 113 is also capable of generating projected yield estimates. Using historical data, environmental conditions, and current crop health data, the device predict the potential yield for the season. This projection help farmers make better planning decisions, such as adjusting resource allocation, modifying planting techniques, or estimating future profits. The AR display might show a visual representation of the projected yield, indicating different areas of the field with high or low yield predictions based on current crop health and growth conditions.

[0066] Moreover, the AR projector 113 supports interactive decision-making. As the farmer interacts with the device through the touch display panel 103, they modify certain parameters or strategies, such as changing the type of treatment or nutrient application. The AR projector 113 dynamically adjusts the projections to reflect the potential outcomes of these changes. This allows farmers to experiment with different strategies and instantly visualize the impact of their decisions, facilitating a trial-and-error approach to optimizing their farming practices without the need for costly physical experiments. The AR projector 113 also aids in spatial analysis of the field. By overlaying detailed maps and projections of the crop’s health and treatment areas onto the actual field, farmers precisely identify where interventions are required. The holographic projections ensure that farmers pinpoint problem areas accurately and avoid unnecessary application of resources. This increases efficiency, reduces waste, and ensures that every part of the field gets the attention it needs, enhancing overall farm productivity

[0067] Lastly, a battery (not shown in figure) is associated with the device to supply power to electrically powered components which are employed herein. The battery is comprised of a pair of electrodes named as a cathode and an anode. The battery uses a chemical reaction of oxidation/reduction to do work on charge and produce a voltage between their anode and cathode and thus produces electrical energy that is used to do work in the device.

[0068] The present invention works best in the following manner, where the device operates through the process that begins with the user providing input via the touch interactive display panel 103 mounted on the housing 101. The microcontroller processes these inputs and activates the track wheels 102 in coordination with the GPS module to navigate the device across the farm field to the specified areas. As the device moves, the artificial intelligence-based imaging unit 104, mounted on the robotic arm 105, captures and analyzes images of the crop leaves to identify any diseases. the color sensor detects color changes and structural patterns indicative of disease, allowing for precise diagnosis. The microcontroller then fetches the appropriate disease management strategy from the linked database, based on the type of disease and crop leaf. Simultaneously, the extendable gripper 106 positions the soil sensor 107 to assess the soil health, providing further context for the treatment. If infected leaves are detected, the four-bar linkage extends the plucker 109 to remove them and store them in the moisture-controlled container 110 for further analysis. The device's storage chamber 111, containing chemicals, nutrients, and growth regulators, is activated based on the microcontroller's evaluation of soil and disease conditions. The machine learning protocol recommends the ideal chemical treatment, which is dispensed through the electronically controlled nozzle 114 onto affected leaves. Nutrients are also released onto the soil as needed. Throughout this process, the augmented reality (AR) projector 113 provides real-time projections of disease spread, treatment effectiveness, and projected crop yield, helping the user make informed decisions to optimize farming practices

[0069] Although the field of the invention has been described herein with limited reference to specific embodiments, this description is not meant to be construed in a limiting sense. Various modifications of the disclosed embodiments, as well as alternate embodiments of the invention, will become apparent to persons skilled in the art upon reference to the description of the invention.
, Claims:1) A crop health monitoring and remediation device, comprising:

i) a housing 101 developed to be positioned on a ground surface of a farm field, wherein plurality of tracks wheels 102 arranged underneath said housing 101 for enabling movement of said housing 101 over said surface;
ii) a touch interactive display panel 103 mounted on said housing 101 for enabling a user to provide input specifications for accessing information about condition of crop leaves of said field, and treat any defected leaves, wherein a microcontroller linked with said display panel 103 for processing said input commands, to actuate said wheels 102 in sync with a GPS (Global Positioning System) module for navigating said housing 101 around said field to said specified areas;
iii) an artificial intelligence-based imaging unit 104 mounted on said housing 101 via a robotic arm 105 that is actuated by said microcontroller to position said imaging unit 104 over said crop leaf, wherein said imaging unit 104 is paired with a processor for capturing and processing multiple images in vicinity of said housing 101, respectively to determine type of said leaves and identify a disease in said leaves;
iv) a database is linked with said microcontroller for storing multiple disease management strategies for specific leaves, that is fetched by said microcontroller for said determined leaf type, wherein said housing 101 is configured with an extendable gripper 106 for positioning a soil sensor 107 embedded in said gripper 106 onto soil to analyze health of said soil, corresponding to unhealthy;
v) a storage chamber 111 arranged on said housing 101 for storing multiple materials including chemicals, nutrients and growth regulators in different sections, wherein said microcontroller evaluates particular amounts of said materials, required to treat said crop, as per said fetched strategy and said soil conditions, in accordance to which said microcontroller actuates a robotic link 112 attached with each of said sections to extend/retract for getting positioned over said leaf;
vi) an electronically controlled nozzle 114 installed at end of said link 112 for dispensing an appropriate amount of said chemical from said chamber 111, over said affected leaf, for ensuring effective and targeted treatment of said leaf, wherein said microcontroller directs nozzle 114 and link 112, associated with said nutrients section, to release nutrients onto soil of said crop, for supplementation; and
vii) an augmented reality (AR) LED holographic projector 113 mounted on upper section of said housing 101 to project visual aids including real time projections of disease dispersion, treatment effectiveness and projected yield of said crop, based on said treatment provided, for enabling said user to view said projections to make informed decisions to optimize farming practices.

2) The device as claimed in claim 1, wherein a color sensor is embedded in said housing 101 and synced with said imaging unit 104 for detecting disease symptoms on said leaves by identifying color changes and structural patterns associated with pests/diseases, for accurately diagnosing said disease affecting said crop.

3) The device as claimed in claim 1, wherein a four-bar linkage arrangement 108 is integrated in between said housing 101 and gripper 106, for enabling extension and retraction of a plucker 109 attached with said arrangement 108, for removing infected leaves from said crop, to store in a container 110, arranged in said housing 101.

4) The device as claimed in claim 1, wherein a moisture sensor is embedded within said container 110 for monitoring moisture levels in said container 110, to ensure ideal conditions for storage to maintain said leaf’s disease characteristics for further analysis.

5) The device as claimed in claim 1, wherein a battery is configured with said device for providing a continuous power supply to electronically powered components associated with said device.