Description:FIELD OF THE INVENTION

[0001] The present invention relates to a system for optimizing irrigation by monitoring plant root zones that is capable of monitor soil conditions near plant roots in real time in order to support accurate irrigation decisions and analyzing soil moisture and nutrient data to understand the specific water and nutrient needs of each plant, thereby ensuring that irrigation decisions are based on actual plant needs.

BACKGROUND OF THE INVENTION

[0002] Agriculture depends heavily on water and nutrients to maintain healthy crop growth and maximize yield. In recent years, increasing awareness of water scarcity and environmental sustainability has highlighted the need for efficient use of resources in farming. Precision agriculture practices aim to monitor and manage the exact needs of crops to reduce waste and improve productivity. Soil and plant monitoring systems have become an important part of this approach, especially when integrated with real-time data collection and decision-making technologies.

[0003] Traditionally, farmers have relied on fixed irrigation schedules or manual observation of soil and crop conditions to decide when and how much to water their fields. These methods are often inaccurate because they do not reflect real-time soil moisture or nutrient levels, especially near the plant root zone where it matters most. Additionally, such methods do not account for environmental changes or differences in individual plant needs, leading to either over-watering or under-watering.

[0004] A major drawback of traditional irrigation systems is the lack of data-driven decision-making. Most conventional systems do not monitor soil nutrient levels or provide plant-specific recommendations. They also lack integration with modern tools such as wireless communication and artificial intelligence, which can help optimize resource use. As a result, there is a risk of water waste, reduced crop health, and lower yield. These limitations create a need for more advanced, automated, and accurate systems that can provide timely and plant-specific irrigation guidance.

[0005] US11833313B2 discloses about system for monitoring and regulating plant productivity comprising: a memory for storing instructions; a processor for executing the instructions to cause a method of monitoring and regulating plant productivity to be performed, the method comprising: receiving field data from monitoring sensors; computing, by the at least one processor executing a machine learning algorithm, a predicted value for a variable associated with the production environment condition of a crop field, the machine learning algorithm having been trained based on a training set comprising one or both of (a) the field data from the monitoring sensors, and (b) a generated feature derived from the field data; and determining, based on a threshold associated with the variable, that the predicted value for the variable indicates that an intervention in the crop field is to be initiated; and in response to the determining, causing a controllable device to vary the production environment condition.

[0006] US10241488B2 discloses about an automated irrigation control comprising crop sensor physically attached to a crop and a light sensitive sensor having a photo-detector for monitoring light intensity of a crop, an irrigation conduit extending along the span of the irrigation zone and adapted to carry fluid, with one or more controllable valves and sensors, growth sensors placed in close proximity of the crop sensors, a computer control system, an irrigation controller, and a communications link between the computer control system, the one or more crop sensor, the three or more growth sensors, and the irrigation controller.

[0007] Conventionally, many systems are available for monitoring plant root zones. However, the cited inventions exhibit certain limitations, where the system lacks in comprehensive real-time monitoring of both moisture and nutrient levels specifically at the root zone. Additionally, they do not fully integrate advanced analytics and adaptive control to provide plant-specific irrigation decisions, leading to inefficiencies in resource use and limited ability to respond dynamically to changing environmental and crop conditions.

[0008] In order to overcome the aforementioned drawbacks, there exists a need in the art to develop a system that enables real-time, root-zone-specific monitoring of both soil moisture and nutrient levels, integrated with artificial intelligence and wireless communication. The system should provide plant-specific irrigation and fertilization recommendations, ensuring precise resource usage, improved crop health, and enhanced yield while addressing sustainability and environmental concerns in modern agriculture practices.

OBJECTS OF THE INVENTION

[0009] The principal object of the present invention is to overcome the disadvantages of the prior art.

[0010] An object of the present invention is to develop a system that is capable of monitoring the condition of soil near plant roots continuously in real time, in order to support more accurate and timely irrigation decisions.

[0011] Another object of the present invention is to develop a system that is capable of analyzing soil moisture and nutrient data in order to identify the exact water and nutrient needs of each plant at different times.

[0012] Another object of the present invention is to develop a system that is capable of reducing the unnecessary use of water and fertilizers by delivering only what is needed to each plant, thereby supporting resource conservation and cost savings.

[0013] 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

[0014] The present invention relates to a system for optimizing irrigation by monitoring plant root zones that is capable of automatically controlling irrigation activities by adjusting the timing and amount of water given to plants based on data analysis and analyzing the soil moisture and nutrient data in order to identify the exact water and nutrient needs of each plant at different times, thereby helping maintain soil health over time.

[0015] According to an embodiment of the present invention, a system for optimizing irrigation by monitoring plant root zones comprising of a network of sensing modules placed in the soil near each plant roots, configured to measure moisture levels and nutrient concentrations in real time, a communication module connected to each the sensing modules, to establish a wireless connection between the sensing module to a central processing unit, to facilitate wireless data transmission to the central processing unit or cloud-based platform associated with the system, an analysis module using artificial intelligence, integrated with the processing unit, configured to process the collected data and determine the water and nutrient needs for each plants, an irrigation control module linked with the processing unit configured to adjust irrigation schedules based on the analysis module’s output to deliver the right amount of water to each plan, a computing unit wirelessly linked with the processing unit, configured to receive notifications from the processing unit, about plant hydration and soil conditions for proactive management and schedules based on the analysis module’s output to deliver the right amount of water to each plant.

[0016] According to another embodiment of the present invention, the system further includes the sensing module includes but not limited to capacitive soil moisture sensors, ion-selective electrodes, near-infrared sensors and NPK sensor, the irrigation control module integrates with existing farming systems to coordinate irrigation with other farm operations and a power module using renewable energy sources, such as solar panels, to supply power to the system.

[0017] 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

[0018] 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 a schematic diagram depicting work flow of a system for optimizing irrigation by monitoring plant root zones.

DETAILED DESCRIPTION OF THE INVENTION

[0019] 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.

[0020] 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.

[0021] 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.

[0022] The present invention relates to a system for optimizing irrigation by monitoring plant root zones that is capable of assisting the user in making better irrigation decisions by providing timely updates and alerts about soil and plant conditions and reducing the unnecessary use of water and fertilizers by delivering only what is needed to each plant, thereby supporting resource conservation and improving plant health and growth.

[0023] Referring to Figure 1, a schematic diagram depicting work flow of a system for optimizing irrigation by monitoring plant root zones is illustrated. The system discloses herein comprising of a network of sensing modules placed in the soil near each plant roots, configured to measure moisture levels and nutrient concentrations in real time. The sensing module includes but not limited to capacitive soil moisture sensors, ion-selective electrodes, near-infrared sensors and NPK sensor.

[0024] These modules are designed to measure soil moisture levels and nutrient concentrations in real time. By continuously collecting data from the root zone, the system provides accurate and timely information about the soil's condition. This enables better decision-making for irrigation and fertilization, helping to ensure that plants receive the right amount of water and nutrients. The real-time monitoring also supports efficient resource usage, reduces waste, and promotes healthier crop development by maintaining optimal growing conditions.

[0025] The capacitive soil moisture sensor measures the volumetric water content in soil by detecting changes in the dielectric permittivity. The sensor consists of two metal plates that form a capacitor. As soil moisture increases, the dielectric constant between the plates changes, altering the capacitance. This change is converted into an electrical signal that correlates with soil moisture levels. Unlike resistive sensors, capacitive sensors are less prone to corrosion and provide more stable readings over time. These sensors are embedded in the soil near plant roots to continuously monitor water availability, enabling efficient irrigation decisions and preventing under- or over-watering.

[0026] The ion-selective electrode measures the concentration of specific ions in the soil solution by converting ion activity into an electrical potential. The electrode consists of a selective membrane that responds only to a target ion, such as potassium or nitrate. When the membrane comes in contact with the soil solution, a voltage is generated proportional to the ion concentration. This voltage is read by a reference electrode and processed into concentration data. ISEs offer high selectivity and real-time measurement of nutrient levels, helping to determine when and how much fertilizer should be applied to support optimal plant growth.

[0027] The near-infrared sensor operates by emitting light in the near-infrared spectrum (typically 700–2500 nm) and measuring the reflected or absorbed light from the soil. Different soil components such as moisture, organic matter, and minerals—absorb and reflect light at characteristic wavelengths. By analyzing the absorption spectra, the sensor can estimate properties like moisture content and organic composition. NIR sensors are non-invasive and can quickly scan large areas. In soil applications, they provide supplementary data to validate other sensor readings and help identify spatial variability in soil properties, supporting precision agriculture and informed soil management practices.

[0028] The NPK sensor measures the concentration of nitrogen (N), phosphorus (P), and potassium (K) in the soil. The sensor typically uses optical, electrochemical, or spectroscopy-based methods to detect nutrient levels. Some NPK sensors rely on colorimetric reactions, where chemical reagents react with soil ions to produce color changes that are measured using photodetectors. Others use ion-selective electrodes or laser-induced breakdown spectroscopy (LIBS). The sensor provides real-time nutrient data, enabling site-specific fertilization strategies. By continuously monitoring NPK values, it ensures optimal nutrient availability for plant growth while minimizing excess fertilizer use, reducing environmental impact and increasing crop yield efficiency.

[0029] Each sensing module collects real-time soil data near plant roots. This data is transmitted wirelessly via a communication module connected to each the sensing modules, to establish a wireless connection between the sensing module to a central processing unit, to facilitate wireless data transmission to the central processing unit or cloud-based platform associated with the system.

[0030] The communication module is responsible for wirelessly transmitting data collected by the sensing modules to the central processing unit or the cloud-based platform. Each sensing module is equipped with a low-power wireless transceiver, such as Lora, ZigBee, Wi-Fi, or Bluetooth, depending on the range and power requirements. These transceivers convert sensor outputs into digital signals and broadcast them over a secure wireless channel. The communication module ensures that real-time data on soil moisture and nutrients is transmitted efficiently, even across large fields. This wireless setup eliminates the need for physical cabling and supports scalability for monitoring multiple plants simultaneously.

[0031] The central processing unit acts as the local control and analytics hub. It receives real-time data wirelessly from all sensing modules via the communication module. The CPU parses, stores, and processes incoming data to assess soil conditions near each plant. Based on programmed logic or adaptive protocols, issue alerts or recommendations for irrigation or fertilization. It also relays data to external interfaces like farm management systems. Positioned either on-site or in a nearby control center, the CPU enables real-time decision-making and reduces latency in critical agricultural operations.

[0032] The cloud-based platform functions as a remote data management and analytics system. Data transmitted from the CPU or directly from the communication module is stored in structured databases for long-term access. Cloud infrastructure supports advanced analytics, machine learning, and visualization tools that help track trends, generate predictive insights, and optimize agricultural practices. The platform ensures secure data backup, remote accessibility, and integration with external tools, enabling informed, data-driven decisions for irrigation, fertilization, and crop planning based on actual soil conditions.

[0033] Post analyzing the received data from the central processing unit, which is sent to an analysis module using artificial intelligence, integrated with the processing unit, configured to process the collected data and determine the water and nutrient needs for each plants.

[0034] The analysis module is integrated with the central processing unit and uses artificial intelligence (AI) to process data collected from the soil sensing modules. This module analyzes parameters such as soil moisture, nutrient levels, temperature, and plant-specific thresholds. By applying machine learning protocols, it identifies patterns and predicts the exact water and nutrient requirements for each plant. The AI model adapts over time by learning from historical data, seasonal trends, and crop types, thereby improving accuracy. It generates real-time recommendations for irrigation and fertilization to individual plant needs. This decision-making process helps reduce resource waste, improves plant health, and supports precision agriculture by delivering targeted care based on actual growing conditions.

[0035] The system includes an irrigation control module linked with the processing unit configured to adjust irrigation schedules based on the analysis module’s output to deliver the right amount of water to each plant. The irrigation control module integrates with existing farming systems to coordinate irrigation with other farm operations.

[0036] The irrigation control module is connected to the processing unit and operates based on instructions received from the analysis module. After the AI-powered analysis module determines the specific water requirements for each plant, the irrigation control module adjusts the watering schedules accordingly. It controls valves, pumps, or drip lines to deliver the right amount of water to each plant zone, preventing over- or under-watering. The module can function in real-time and is capable of zone-wise or plant-wise control, depending on system configuration. The module ensures efficient water usage by aligning irrigation actions with actual soil conditions and plant needs.

[0037] Further the collected data from both the modules are transmitted to a computing unit wirelessly linked with the processing unit, configured to receive notifications from the processing unit, about plant hydration and soil conditions for proactive management and schedules based on the analysis module’s output to deliver the right amount of water to each plant.

[0038] The computing unit is wirelessly linked to the processing unit and serves as a user interface to receive real-time notifications from the processing unit regarding plant hydration status, soil moisture, and nutrient levels. These alerts are based on data processed by the analysis module, which determines the precise water and nutrient needs for each plant. The computing unit displays this information through the user interface, allowing users to monitor field conditions remotely. By providing timely insights and control options, the computing unit helps users make informed decisions, optimize resource use, and maintain optimal plant health with minimal manual intervention, enhancing the efficiency of precision agriculture.

[0039] The system further comprising a power module using renewable energy sources, such as solar panels, to supply power to the system. This module generates electrical power from sunlight and distributes it to various components of the system, including sensing modules, communication units, and processing elements. The use of solar energy ensures continuous, self-sustained operation even in remote or off-grid agricultural areas. The power module may include a battery storage system to store excess energy generated during the day, ensuring uninterrupted operation during nighttime or cloudy conditions. By using renewable energy, the system minimizes reliance on external power sources, reduces operational costs, and supports environmentally sustainable farming practices.

[0040] The present invention works best in the following manner, where the system comprising of the sensing module placed in the soil near plant roots, connected to the communication module, configured to measure and transmit real-time soil moisture and nutrient data. The sensing module includes the capacitive soil moisture sensor, ion-selective electrode, near-infrared sensor, and NPK sensor. The capacitive sensor detects changes in soil water content through dielectric permittivity; the ion-selective electrode measures specific ion concentrations via selective membranes; the near-infrared sensor evaluates soil composition based on reflected light and the NPK sensor determines nitrogen, phosphorus, and potassium levels using optical or electrochemical methods. These measurements are transmitted wirelessly via the communication module, which uses low-power transceivers like Lora, ZigBee, Wi-Fi, or Bluetooth to connect with the central processing unit.

[0041] In continuation with the central processing unit, serving as the local analytics hub, receives and processes sensor data to assess soil conditions and sends the data to the cloud-based platform for advanced analysis, long-term storage, and remote access. The analysis module integrated with the processing unit uses artificial intelligence to interpret the data, identify patterns, and determine specific water and nutrient needs for each plant. The irrigation control module connected to the processing unit receives instructions from the analysis module to adjust watering schedules and operate valves or pumps for precise irrigation. The computing unit wirelessly linked to the processing unit receives notifications about plant hydration and soil conditions to support proactive farm management. The power module, using solar panels with optional battery storage, supplies renewable energy to all system components.

[0042] 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 system for optimizing irrigation by monitoring plant root zones, comprising:

i) a network of sensing modules placed in the soil near each plant roots, configured to measure moisture levels and nutrient concentrations in real time;
ii) a communication module connected to each the sensing modules, to establish a wireless connection between the sensing module to a central processing unit, to facilitate wireless data transmission to the central processing unit or cloud-based platform associated with the system;
iii) an analysis module using artificial intelligence, integrated with the processing unit, configured to process the collected data and determine the water and nutrient needs for each plants;
iv) an irrigation control module linked with the processing unit configured to adjust irrigation schedules based on the analysis module’s output to deliver the right amount of water to each plant; and
v) a computing unit wirelessly linked with the processing unit, configured to receive notifications from the processing unit, about plant hydration and soil conditions for proactive management and schedules based on the analysis module’s output to deliver the right amount of water to each plant.

2) The system as claimed in claim 1, wherein the sensing module includes but not limited to capacitive soil moisture sensors, ion-selective electrodes, near-infrared sensors and NPK sensor.

3) The system as claimed in claim 1, wherein the data transmission module uses wireless communication to send data to the cloud-based platform.

4) The system as claimed in claim 1, wherein the irrigation control module integrates with existing farming systems to coordinate irrigation with other farm operations.

5) The system as claimed in claim 1, wherein the system further comprising a power module using renewable energy sources, such as solar panels, to supply power to the system.