1. A microbial activity monitoring and irrigation system (100) for soil, the monitoring and irrigation system (100) comprising: a user interface (102) integrated with a user device (104), the user interface (102) configured to acquire input commands related to soil monitoring and irrigation management; a plurality of wireless sensor probes (106) inserted within the soil, connected to the user interface (102) via a communication unit (140), the wireless sensor probes (106) configured to monitor microbial activity within the soil; an irrigation unit (108) integrated with the system (100) for irrigating the soil as per requirement; a communication network (110) configured to provide bidirectional data transmission within the system (100); a processing unit (112) connected to the plurality of wireless sensor probes (106) and the irrigation unit (108)via the communication network (110), the processing unit (112) configured to process real-time data for microbial activity monitoring and irrigation, wherein the processing unit (112) further comprises; an input module (116) configured to receive real-time data from the plurality of wireless sensor probes (106); a pre-processing module (118) configured to pre-process received data into machine readable format for further analysis; a monitoring module (122) configured to receive and process signals from the plurality of wireless sensor probes (106) to compute a Microbial Activity Index (MAI) for quantifying soil biological activity; a comparison module (124) configured to compare the determined Microbial Activity Index (MAI) against a predefined threshold index to evaluate soil biological status and generate control signals for optimizing irrigation management; a prediction module (126) configured to analyse soil biological status and forecast irrigation requirements to determine an optimized water application volume for improving microbial stability and enhancing soil fertility; an irrigation control module (128) configured to regulate operation of the irrigation unit (108) in accordance with the predicted irrigation requirement to maintain optimal soil moisture balance; an alert generation module (134) configured to generate and transmit real-time notifications related to microbial activity deviations and irrigation parameters to provide timely user intervention; an output module (138) configured to transmit processed data to the user interface (102) for real-time monitoring, analysis, and informed irrigation decision-making;

2. The monitoring and irrigation system (100) as claimed in claim 1, wherein the system (100) further comprises a cloud database (114) configured to securely store, manage, and transmit retrieved input data for subsequent operations.

3. The system (100) as claimed in claim 1, wherein each of the wireless sensor probes (106) further comprises a oxygen (O2) sensor to monitor the oxygen concentration within the soil, a carbon dioxide (CO2) sensor to monitor carbon dioxide concentration, a electrochemical sensor to detect the presence of metabolic byproducts within the soil, a moisture sensor to detect the amount of moisture present within the soil, indicative of microbial respiration.

4. The system (100) as claimed in claim 1, wherein the user interface (102) is further configured to acquire key soil parameters including soil moisture level, temperature, microbial activity data, irrigation preferences, and user-defined irrigation control inputs.

5. The system (100) as claimed in claim 1, wherein the user interface (102) further comprises a chatbot (136) configured to interact with users by providing real-time soil health status, microbial activity insights, irrigation recommendations, assisting in data entry, retrieving historical soil records, and explaining irrigation decisions.

6. The system (100) as claimed in claim 1, wherein the system (100) includes a solar energy-harvesting unit configured to generate and store electrical power for operating the system (100) for providing continuous operation.

7. The system (100) as claimed in claim 1, wherein the processing unit (112) further comprises a training and testing module (130) configured to partition processed sensor data into training and testing datasets and iteratively train and refine a machine learning model to improve prediction accuracy for irrigation management.

8. The system (100) claimed in claim 1, wherein the processing unit (112) further comprises a data logging module (132) configured to organize and store input data from the wireless sensor probes (106) and user interface (102) into structured classifications for efficient analysis, historical tracking, and irrigation decision support.

9. The system (100) as claimed in claim 1, wherein the irrigation unit (108) comprises a pump assembly, a network of distribution pipelines, and a plurality of controllable valves configured to deliver water to the soil in accordance with control signals generated by the irrigation control module (128).

10. A method (400) for making a storage bag (100), the method (400) comprising: acquiring soil monitoring and irrigation-related inputs via a user interface (102) integrated with a user device (104); transmitting data between several components of the system (100) via a communication network (110); processing received sensor data and user inputs to evaluate soil biological status via a processing unit (112) comprising several modules; receiving input commands from the user interface (102) via an input module (116); pre-processing collected sensor data by filtering noise, normalizing sensor values, and converting the data into a machine-readable format via a pre-processing module (118); detecting microbial activities within soil via the wireless sensor probes (106); monitoring a Microbial Activity Index (MAI) to quantify soil biological activity via a monitoring module (122); comparing the determined Microbial Activity Index (MAI) with a predefined threshold index to evaluate the soil biological condition via a comparison module (124); predicting an optimized irrigation requirement based on the evaluated soil biological status via a prediction module (126); controlling operation of an irrigation unit (108) to deliver water to the soil according to the predicted irrigation requirement via an irrigation control module (128); generating real-time alerts when deviations in microbial activity and irrigation parameters are detected via an alert generation module (134); logging input data into a cloud database (114) in a structured classification via a data logging module (132); separating processed sensor data into training and testing datasets via a training and testing module (130); and transmitting processed soil condition data, irrigation decisions, and system (100) alerts to the user interface (102) via an output module (138).

Description:FIELD OF DISCLOSURE
[0001] The present disclosure generally relates to soil monitoring and irrigation management, more specifically, relates to microbial activity monitoring and irrigation system based on assessment of soil biological activity to support efficient irrigation management and improved soil condition.
BACKGROUND OF THE DISCLOSURE
[0002] Soil microbial activity plays an important role in maintaining soil fertility, nutrient cycling, and overall crop productivity. However, farmers often face difficulty in understanding the biological condition of soil because microbial processes are not easily visible or measurable through conventional soil monitoring methods.
[0003] Traditional irrigation practices are commonly based only on moisture levels or fixed schedules, which leads to excessive and insufficient watering, thereby disturbing microbial balance and soil health. Variations in temperature, moisture, and gas exchange within the soil further influence microbial activity, making proper irrigation decisions challenging. In addition, lack of real-time monitoring and limited access to reliable soil condition information restrict effective management of irrigation, leading to inefficient water use and reduced agricultural productivity
[0004] Several soil monitoring devices and systems are currently available for assessing soil conditions and microbial activity. Conventional systems measure soil respiration by analysing gas exchange and microbial decomposition processes. However, these instruments are primarily designed for laboratory and research environments and often require manual sampling, specialized setup, and high operational cost.
[0005] As a result, existing solutions provide limited real-time field monitoring, lack integration with irrigation decision systems, and often fail to deliver continuous soil biological activity assessment required for efficient irrigation management.
[0006] The present invention overcomes the limitations of the prior art by providing a soil monitoring and irrigation management system configured to evaluate soil biological activity in real time for supporting effective irrigation decisions. The system processes multiple soil parameters to determine the level of microbial activity and associated soil conditions. By providing automated analysis and timely evaluation of soil biological status, the system reduces reliance on manual observation, improves irrigation planning, and supports balanced soil moisture conditions. This approach contributes to better soil fertility, efficient water usage, and improved overall soil health management.
[0007] Thus, in light of the above-stated discussion, there exists a need for a microbial activity monitoring and irrigation system.
SUMMARY OF THE DISCLOSURE
[0008] The following is a summary description of illustrative embodiments of the invention. It is provided as a preface to assist those skilled in the art to more rapidly assimilate the detailed design discussion which ensues and is not intended in any way to limit the scope of the claims which are appended hereto in order to particularly point out the invention.
[0009] According to illustrative embodiments, the present disclosure focuses on a microbial activity monitoring and irrigation system which overcomes the above-mentioned disadvantages or provide the users with a useful or commercial choice.
[0010] The present invention solves all the above major limitations of a real-time microbial activity monitoring and irrigation system.
[0011] An objective of the present disclosure is to provide a system for monitoring soil biological activity and evaluating soil conditions in order to support efficient irrigation management and improve soil health and water utilization.
[0012] Another objective of the present disclosure is to provide a method for determining a soil biological activity for accurately assessing soil health conditions and enabling improved irrigation planning for maintaining balanced soil productivity.
[0013] Another objective of the present disclosure is to provide an approach for comparing the determined soil biological activity with predefined reference values to detect deviations in soil condition and support appropriate irrigation decision-making for maintaining soil stability.
[0014] Another objective of the present disclosure is to provide a system for predicting irrigation requirements based on evaluated soil biological status in order to support proper water application and maintain balanced soil moisture conditions.
[0015] Another objective of the present disclosure is to optimize water application based on soil condition assessment in order to maintain balanced soil moisture levels and support improved soil health and irrigation efficiency.
[0016] Another objective of the present disclosure is to provide an approach for maintaining stable microbial activity within the soil in order to improve soil fertility, support balanced biological conditions, and promote sustainable soil health management.
[0017] Yet another objective of the present disclosure is to provide a method for generating real-time information related to soil biological condition and irrigation requirements in order to support timely monitoring, informed decision-making, and efficient irrigation management.
[0018] Yet another objective of the present disclosure is to provide an approach for maintaining historical soil monitoring data for further analysis in order to support long-term soil assessment, trend identification, and improved irrigation decision-making.
[0019] In light of the above, in one aspect of the present disclosure, a microbial activity monitoring and irrigation system is disclosed herein. The system comprises a user interface integrated with a user device, the user interface configured to acquire input commands related to soil monitoring and irrigation management. The system includes a plurality of wireless sensor probes inserted within the soil, connected to the user interface via a communication unit, the wireless sensor probes configured to monitor microbial activity within the soil. The system also includes an irrigation unit integrated with the system for irrigating the soil as per requirement. The system also includes a communication network configured to provide bidirectional data transmission within the system. The system also includes a processing unit connected to the plurality of wireless sensor probes and the irrigation unit via the communication network, the processing unit configured to process real-time data for microbial activity monitoring and irrigation, wherein the processing unit further comprises an input module configured to receive real-time data from the plurality of wireless sensor probes, a pre-processing module configured to pre-process received data into machine readable format for further analysis, a monitoring module is configured to receive and process signals from the plurality of wireless sensor probes 106 to compute a Microbial Activity Index (MAI) for quantifying soil biological activity, a comparison module configured to compare the determined Microbial Activity Index (MAI) against a predefined threshold index to evaluate soil biological status and generate control signals for optimizing irrigation management, a prediction module configured to analyse soil biological status and forecast irrigation requirements to determine an optimized water application volume for improving microbial stability and enhancing soil fertility, an irrigation control module configured to regulate operation of the irrigation unit in accordance with the predicted irrigation requirement to maintain optimal soil moisture balance, an alert generation module configured to generate and transmit real-time notifications related to microbial activity deviations and irrigation parameters to provide timely user intervention and an output module configured to transmit processed data to the user interface for real-time monitoring, analysis, and informed irrigation decision-making.
[0020] In one embodiment, the system further comprises a cloud database configured to securely store, manage, and transmit retrieved input data for subsequent operations.
[0021] In one embodiment, each of the wireless sensor probes further comprises a oxygen (O2) sensor to monitor the oxygen concentration within the soil, a carbon dioxide (CO2) sensor to monitor carbon dioxide concentration, a electrochemical sensor to detect the presence of metabolic byproducts within the soil, a moisture sensor to detect the amount of moisture present within the soil, indicative of microbial respiration.
[0022] In one embodiment, the user interface is further configured to acquire key soil parameters including soil moisture level, temperature, microbial activity data, irrigation preferences, and user-defined irrigation control inputs.
[0023] In one embodiment, the user interface further comprises a chatbot 136 configured to interact with users by providing real-time soil health status, microbial activity insights, and irrigation recommendations, assisting in data entry, retrieving historical soil records, and explaining irrigation decisions.
[0024] In one embodiment, the system includes a solar energy-harvesting unit configured to generate and store electrical power for operating the system for providing continuous operation.
[0025] In one embodiment, the processing unit further comprises a training and testing module configured to partition processed sensor data into training and testing datasets and iteratively train and refine a machine learning model to improve prediction accuracy for irrigation management.
[0026] In one embodiment, the processing unit further comprises a data logging module configured to organize and store input data from the wireless sensor probes and user interface into structured classifications for efficient analysis, historical tracking, and irrigation decision support.
[0027] In one embodiment, the irrigation unit comprises a pump assembly, a network of distribution pipelines, and a plurality of controllable valves configured to deliver water to the soil in accordance with control signals generated by the irrigation control module.
[0028] In light of the above, in another aspect of the present disclosure, a method for microbial activity monitoring and irrigation is disclosed herein. The method comprises acquiring soil monitoring and irrigation-related inputs via a user interface integrated with a user device. The method also includes transmitting data between several components of the system via a communication network. The method also includes processing received sensor data and user inputs to evaluate soil biological status via a processing unit comprising several modules. The method also includes receiving input commands from the user interface via an input module. The method also includes pre-processing collected sensor data by filtering noise, normalizing sensor values, and converting the data into a machine-readable format via a pre-processing module. The method also includes activating a plurality of wireless sensor probes to monitor microbial activity via a sensor activation module. The method also includes detecting microbial activities within soil via the wireless sensor probes. The method also includes calculating a Microbial Activity Index (MAI) to quantify soil biological activity via a monitoring module. The method also includes comparing the determined Microbial Activity Index (MAI) with a predefined threshold index to evaluate the soil biological condition via a comparison module. The method also includes predicting an optimized irrigation requirement based on the evaluated soil biological status via a prediction module. The method also includes controlling operation of an irrigation unit to deliver water to the soil according to the predicted irrigation requirement via an irrigation control module. The method also includes generating real-time alerts when deviations in microbial activity and irrigation parameters are detected via an alert generation module. The method also includes logging input data into a cloud database in a structured classification via a data logging module. The method also includes separating processed sensor data into training and testing datasets via a training and testing module. The method also includes transmitting processed soil condition data, irrigation decisions, and system alerts to the user interface via an output module.
[0029] These and other advantages will be apparent from the present application of the embodiments described herein.
[0030] 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 utilizing, alone or in combination, one or more of the features set forth above or described in detail below.
[0031] These elements, together with the other aspects of the present disclosure and various features are pointed out with particularity in the claims annexed hereto and form a part of the present disclosure. For a better understanding of the present disclosure, its operating advantages, and the specified object attained by its uses, reference should be made to the accompanying drawings and descriptive matter in which there are illustrated exemplary embodiments of the present disclosure.
BRIEF DESCRIPTION OF THE DRAWINGS
[0032] To describe the technical solutions in the embodiments of the present disclosure or in the prior art more clearly, the following briefly describes the accompanying drawings required for describing the embodiments or the prior art. Apparently, the accompanying drawings in the following description merely show some embodiments of the present disclosure, and a person of ordinary skill in the art can derive other implementations from these accompanying drawings without creative efforts. All of the embodiments or the implementations shall fall within the protection scope of the present disclosure.
[0033] The advantages and features of the present disclosure will become better understood with reference to the following detailed description taken in conjunction with the accompanying drawing, in which:
[0034] FIG. 1 illustrates a block diagram of a microbial activity monitoring and irrigation system, in accordance with an exemplary embodiment of the present disclosure;
[0035] FIG. 2 illustrates a method for optimized microbial activity monitoring and irrigation, in accordance with an exemplary embodiment of the present disclosure.
[0036] Like reference, numerals refer to like parts throughout the description of several views of the drawing.
[0037] The microbial activity monitoring and irrigation system is illustrated in the accompanying drawings, which like reference letters indicate corresponding parts in the various figures. It should be noted that the accompanying figure is intended to present illustrations of exemplary embodiments of the present disclosure. This figure is not intended to limit the scope of the present disclosure. It should also be noted that the accompanying figure is not necessarily drawn to scale.
DETAILED DESCRIPTION OF THE DISCLOSURE
[0038] The following is a detailed description of embodiments of the disclosure depicted in the accompanying drawings. The embodiments are in such detail as to communicate the disclosure. However, the amount of detail offered is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present disclosure.
[0039] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. It may be apparent to one skilled in the art that embodiments of the present disclosure may be practiced without some of these specific details.
[0040] Various terms as used herein are shown below. To the extent a term is used, it should be given the broadest definition persons in the pertinent art have given that term as reflected in printed publications and issued patents at the time of filing.
[0041] The terms “a” and “a” herein do not denote a limitation of quantity, but rather denote the presence of at least one of the referenced items.
[0042] The terms “having”, “comprising”, “including”, and variations thereof signify the presence of a component.
[0043] Referring now to FIG. 1 to FIG. 2 to describe various exemplary embodiments of the present disclosure. FIG. 1 illustrates a perspective view of a microbial activity monitoring and irrigation system 100, in accordance with an exemplary embodiment of the present disclosure.
[0044] The system 100 may include a user interface 102, a user device 104, a plurality of wireless sensor probes 106, an irrigation unit 108, a communication network 110 and a processing unit 112.
[0045] In one embodiment of the present invention, the system 100 further comprises a cloud database 114 configured to securely store, manage, and transmit retrieved input data for subsequent operations.
[0046] The user interface 102 integrated with a user device 104. The user interface 102 is configured to acquire input commands related to soil monitoring and irrigation management.
[0047] In one embodiment of the present invention, the soil monitoring and irrigation-related input commands are typically entered by the user who collects, verifies, and inputs relevant soil parameters, environmental conditions, and irrigation preferences through the user interface 102 for further processing and analysis.
[0048] In one embodiment of the present invention, the user interface 102 enables users to securely access the system 100 through a login interface by entering authentication credentials, thereby allowing only authorized users to access soil monitoring data and irrigation management functions.
[0049] In one embodiment, the user interface 102 is implemented as a web-based and mobile application accessible via standard internet browsers.
[0050] In one embodiment, the user interface 102 is implemented as a web-based or mobile application accessible through standard internet browsers for providing a remotely monitor soil biological activity, view irrigation recommendations and manage irrigation operations in real time.
[0051] In one embodiment of the present invention, the user device 104 may include a smartphone, a tablet, a laptop, a personal computer, a desktop computer, a smart device, and any other internet-enabled electronic device capable of supporting user interaction and secure communication with the system 100.
[0052] In one embodiment of the present invention, the user interface 102 further comprises a chatbot 136 configured to interact with users by providing real-time soil health status, microbial activity information, irrigation recommendations, assisting in data entry, retrieving historical soil data, and explaining irrigation decisions.
[0053] In one embodiment of the present invention, the chatbot 136 provides multi-language support to allow users to interact with the system 100 in their preferred language.
[0054] In one embodiment of the present invention, the chatbot 136 is configured to operate via voice and text-based functionalities.
[0055] The plurality of wireless sensor probes 106 inserted within the soil, connected to the user interface 102 via a communication unit 140. The wireless sensor probes 106 configured to monitor microbial activity within the soil. In one embodiment of the present invention, the wireless sensor probes 106 detect variations in soil gas concentration, electrochemical activity, and moisture conditions associated with microbial processes occurring within the soil.
[0056] The irrigation unit 108 integrated with the system 100 for irrigating the soil as per requirement. In one embodiment of the present invention, the controlled irrigation supports proper microbial activity, prevents excessive and insufficient watering, and helps to maintain balanced soil conditions for improved soil productivity.
[0057] The communication network 110 configured to provide bidirectional data transmission within the system 100.
[0058] In one embodiment of the present invention, the communication network 110 may be both wired and wireless.
[0059] In one embodiment of the present invention, the communication netwrok utilizes LoRa or Wi-Fi module to support reliable and long-range wireless data transfer. The communication network 110 transmits collected sensor data to the cloud dashboard through the communication network 110.
[0060] The processing unit 112 connected to the plurality of wireless sensor probes 106 and the irrigation unit 108 via the communication network 110. The processing unit 112 configured to process real-time data for microbial activity monitoring and irrigation. The processing unit 112 further comprises an input module 116, a pre-processing module 118, a monitoring module 122, a comparison module 124, a prediction module 126, an irrigation control module 128, a training and testing module 130, a data logging module 132, an alert generation module 134 and an output module 138.
[0061] The input module 116 configured to receive real-time data from the plurality of wireless sensor probes 106. The data input module 116 acts as the initial gateway of the processing unit 112 for capturing all relevant soil monitoring information received from the wireless sensor probes 106 for further processing.
[0062] The pre-processing module 118 is configured to pre-process input data into machine readable format for further analysis. The pre-processing module 118 perform operations such as filtering noise from raw sensor signals, normalizing measured values, and organizing the collected data into a structured and machine-readable format. The pre-processing module 118 improves data consistency and reliability.
[0063] In one embodiment of the present invention, the wireless sensor probes 106 further comprises a oxygen (O2) sensor to monitor the oxygen concentration within the soil, a carbon dioxide (CO2) sensor to monitor carbon dioxide concentration, a electrochemical sensor to detect the presence of metabolic byproducts within the soil, a moisture sensor to detect the amount of moisture present within the soil, indicative of microbial respiration.
[0064] The oxygen sensor operates based on electrochemical sensing principles, wherein oxygen molecules interact with the sensing element to generate a measurable electrical signal proportional to oxygen levels. Monitoring soil oxygen helps indicate microbial respiration and soil aeration conditions, thereby supporting accurate assessment of soil biological activity.
[0065] The carbon dioxide sensor typically operates based on non-dispersive infrared (NDIR) sensing principles, wherein CO₂ molecules absorb infrared radiation at specific wavelengths to produce a measurable signal proportional to CO₂ levels. The detected concentration reflects microbial respiration activity, thereby assisting in evaluating soil biological processes and overall soil health conditions.
[0066] The electrochemical sensor operates based on electrochemical reactions occurring at sensing electrodes, where target compounds generated by microbial metabolism undergo oxidation or reduction, producing measurable electrical signals. The generated signals correspond to the concentration of metabolic compounds, thereby enabling detection of microbial activity and assessment of soil biological conditions.
[0067] The moisture sensor typically operates based on resistive sensing principles, wherein variations in soil water content alter the electrical capacitance or resistance of the sensing element. The measured signal corresponds to soil moisture levels, thereby assisting in assessing soil hydration conditions and supporting efficient irrigation management.
[0068] In one embodiment of the present invention, the monitoring of microbial activity assists in understanding soil health conditions and supports informed irrigation management, thereby providing optimized water application and maintaining balanced soil biological activity.
[0069] The monitoring module 122 is configured to receive and process signals from the plurality of wireless sensor probes 106 to compute a Microbial Activity Index (MAI) for quantifying soil biological activity.
[0070] In one embodiment of the present invention, the monitoring module 122 analyzes variations in parameters such as oxygen concentration, carbon dioxide concentration, electrochemical responses, and soil moisture conditions that are associated with microbial metabolic processes. Based on the processed sensor data, the monitoring module 122 computes a Microbial Activity Index (MAI), which represents a quantitative indicator of the level of biological activity occurring within the soil. The calculated Microbial Activity Index (MAI) assists in assessing soil biological status and provides a reliable basis for evaluating soil health and supporting irrigation management decisions.
[0071] The comparison module 124 is configured to compare the determined Microbial Activity Index (MAI) against a predefined threshold index to evaluate soil biological status and generate control signals for optimizing irrigation management.
[0072] In one embodiment of the present invention, the comparison module 124 analyses whether the measured microbial activity falls within, above, or below the predefined range. Based on the analysed comparison, the comparison module 124 determines the current biological status of the soil and identifies possible variations in microbial activity.
[0073] The prediction module 126 is configured to analyse soil biological status and forecast irrigation requirements to determine an optimized water application volume for improving microbial stability and enhancing soil fertility.
[0074] In one embodiment of the present invention, when the current biological status deviations from the threshold values, the comparison module 124 generates appropriate control signals that are transmitted to the prediction module 126 for further processing.
[0075] In one embodiment of the present invention, the prediction module 126 determines an optimized quantity of water required to maintain balanced soil moisture and support stable microbial activity. By forecasting irrigation needs according to soil biological behaviour and moisture conditions, the prediction module 126 assists in preventing excessive and insufficient watering.
[0076] The irrigation control module 128 is configured to regulate operation of the irrigation unit 108 in accordance with the predicted irrigation requirement to maintain optimal soil moisture balance.
[0077] In one embodiment of the present invention, the irrigation unit 108 comprises a pump assembly, a network of distribution pipelines, and a plurality of controllable valves configured to deliver water to the soil in accordance with control signals generated by the irrigation control module 128.
[0078] In one embodiment of the present invention, the irrigation module receives control signals generated after evaluation of the soil biological status and determines the appropriate timing and quantity of water to be supplied to the soil.
[0079] In one embodiment of the present invention, based on the determined timing and quantity of water to be supplied to the soil. Post determining the timing and quantity, the irrigation control module 128 activates the irrigation unit 108 to supply water to the soil in a controlled manner. The controlled activation of the irrigation unit 108 ensures that the soil receives the required amount of moisture, thereby maintaining balanced soil conditions and supporting stable microbial activity for improved soil health.
[0080] In one embodiment of the present invention, the pump assembly draws water from a storage source and supplies the drawn water through the distribution pipelines. The pipelines transport water to different regions of the soil field, while the controllable valves regulate the flow of water based on control signals generated by the irrigation control module 128. By selectively opening and closing the valves, the irrigation unit 108 delivers a controlled quantity of water to the soil to ensure accurate irrigation, maintains suitable soil moisture levels, and supports stable microbial activity within the soil.
[0081] In one embodiment of the present invention, the controlled irrigation prevents excessive water application and moisture deficiency, thereby supporting balanced soil conditions and maintaining stable microbial activity necessary for sustaining soil health and agricultural productivity.
[0082] In one embodiment of the present invention, the user interface 102 is further configured to acquire key soil parameters including soil moisture level, temperature, microbial activity data, irrigation preferences, and user-defined irrigation control inputs.
[0083] In one embodiment of the present invention, processing unit 112 further comprises a data logging module 132 configured to organize and store input data from the wireless sensor probes 106 and user interface 102 into structured classifications for efficient analysis, historical tracking, and irrigation decision support.
[0084] In one embodiment of the present invention, the collected data is structured into categorized datasets and stored within the cloud database 114. The structured logging of the data provides efficient retrieval for analysis, supports historical monitoring of soil biological conditions, and assists in improving irrigation decision-making. Furthermore, the stored datasets facilitate model training, system 100 diagnostics, and long-term evaluation of soil health and irrigation performance.
[0085] In one embodiment of the present invention, the processing unit 112 further comprises a training and testing module 130 configured to partition processed sensor data into training and testing datasets and iteratively train and refine a machine learning model to improve prediction accuracy for irrigation management.
[0086] In one embodiment of the present invention, the training dataset is utilized to train the machine learning model that learns relationships between soil parameters such as moisture, oxygen concentration, carbon dioxide level, and microbial activity. The testing dataset is subsequently used to evaluate the performance and accuracy of the trained model. Based on iterative training, validation, and error correction, the training and testing module 130 continuously refines the prediction module 126 to improve reliability in forecasting irrigation requirements, thereby enabling adaptive and data-driven irrigation management for maintaining optimal soil biological conditions.
[0087] The alert generation module 134 is configured to generate and transmit real-time notifications related to microbial activity deviations and irrigation parameters to provide timely user intervention.
[0088] In one embodiment of the present invention, when microbial activity levels fall below/exceed predefined limits and when irrigation conditions deviate from the predicted requirement, the alert generation module 134 automatically generates real-time alerts.
[0089] In one embodiment of the present invention, the alerts are transmitted to the user interface 102 of the user device 104 through the communication network 110 in the form of push notifications, messages and dashboard indicators. The alerts enable the users to take timely corrective actions, ensuring optimal soil biological balance and efficient irrigation management.
[0090] The output module 138 is configured to transmit processed data to the user interface 102 for real-time monitoring, analysis, and informed irrigation decision-making.
[0091] In one embodiment of the present invention, the output module 138 converts analytical results generated by the processing unit 112 into a structured and user-readable format suitable for real-time visualization. Such information is presented through dashboards, graphical indicators, status notifications, and summarized reports to assist the user in understanding the current soil biological condition and irrigation requirements.
[0092] In one embodiment of the present invention, the system 100 includes a solar energy-harvesting unit configured to generate and store electrical power for operating the system 100 for providing continuous operation.
[0093] In one embodiment of the present invention, the solar energy-harvesting unit comprises one or more photovoltaic panels configured to convert incident solar radiation into electrical energy. The generated electrical energy is regulated through a charge controller and stored within a rechargeable battery unit to ensure stable power availability. The stored energy is utilized to power the processing unit 112, wireless sensor probes 106, communication modules, and irrigation control components.
[0094] FIG. 2 illustrates a method 200 for optimized microbial activity monitoring and irrigation, in accordance with an exemplary embodiment of the present disclosure.
[0095] The method 200 may include the following steps:
[0096] At step 202, acquire soil monitoring and irrigation-related inputs via a user interface 102 integrated with a user device 104.
[0097] At step 204, transmit data between several components of the system 100 via a communication network 110.
[0098] At step 206, pre-process received sensor data and user inputs to evaluate soil biological status via a processing unit 112 comprising several modules.
[0099] At step 208, receive input commands from the user interface 102 via an input module 116.
[0100] At step 210, pre-process collected sensor data by filtering noise, normalizing sensor values, and converting the data into a machine-readable format via a pre-processing module 118.
[0101] At step 212, detect microbial activities within soil via the wireless sensor probes 106.
[0102] At step 214, monitor a Microbial Activity Index (MAI) to quantify soil biological activity via a monitoring module 122.
[0103] At step 216, compare the determined Microbial Activity Index (MAI) with a predefined threshold index to evaluate the soil biological condition via a comparison module 124.
[0104] At step 218, predict an optimized irrigation requirement based on the evaluated soil biological status via a prediction module 126.
[0105] At step 220, control operation of an irrigation unit 108 to deliver water to the soil according to the predicted irrigation requirement via an irrigation control module 128.
[0106] At step 222, generate real-time alerts when deviations in microbial activity and irrigation parameters are detected via an alert generation module 134.
[0107] At step 224, log input data into a cloud database 114 in a structured classification via a data logging module 132.
[0108] At step 226, separate processed sensor data into training and testing datasets via a training and testing module 130.
[0109] At step 226, transmit processed soil condition data, irrigation decisions, and system 100 alerts to the user interface 102 via an output module 138.
[0110] In the best mode of operation, the microbial activity monitoring and irrigation system 100 operates as an intelligent, end-to-end platform designed to streamline and optimize irrigation in soil fields. The system 100 functioning beings by acquiring soil monitoring inputs and irrigation-related commands through a user interface 102 integrated with a user device 104. The received data is transmitted through a communication network 110 to a processing unit 112, where an input module 116 receives the commands and a pre-processing module 118 filters noise, normalizes sensor readings, and converts the data into a machine-readable format. A plurality of wireless sensor probes 106 positioned within the soil to monitor microbial activity by detecting variations in soil gas concentration, electrochemical signals, and moisture levels. The collected signals are processed by a monitoring module 122 to compute a Microbial Activity Index (MAI) representing soil biological activity. A comparison module 124 evaluates the calculated MAI against predefined threshold values to determine soil biological condition. Based on this evaluation, a prediction module 126 determines an optimized irrigation requirement. An irrigation control module 128 accordingly regulates operation of the irrigation unit 108 to deliver water in a controlled manner. Simultaneously, an alert generation module 134 produces notifications when deviations in microbial activity or irrigation parameters occur. The system 100 further logs the monitoring data in a cloud database 114 and separates the processed data into training and testing datasets for improving prediction accuracy. Finally, the processed soil condition information, irrigation decisions, and alerts are transmitted to the user interface 102 for real-time monitoring and informed irrigation management.
[0111] While the invention has been described in connection with what is presently considered to be the most practical and various embodiments, it will 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.
[0112] A person of ordinary skill in the art may be aware that, in combination with the examples described in the embodiments disclosed in this specification, units and algorithm steps may be implemented by electronic hardware, computer software, or a combination thereof.
[0113] The foregoing descriptions of specific embodiments of the present disclosure have been presented for purposes of illustration and description. They are not intended to be exhaustive or to limit the present disclosure to the precise forms disclosed, and many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described to best explain the principles of the present disclosure and its practical application, and to thereby enable others skilled in the art to best utilize the present disclosure and various embodiments with various modifications as are suited to the particular use contemplated. It is understood that various omissions and substitutions of equivalents are contemplated as circumstances may suggest or render expedient, but such omissions and substitutions are intended to cover the application or implementation without departing from the scope of the present disclosure.
[0114] Disjunctive language such as the phrase “at least one of X, Y, Z,” unless specifically stated otherwise, is otherwise understood with the context as used in general to present that an item, term, etc., may be either X, Y, or Z, or any combination thereof (e.g., X, Y, and/or Z). Thus, such disjunctive language is not generally intended to, and should not, imply that certain embodiments require at least one of X, at least one of Y, or at least one of Z to each be present.
[0115] In a case that no conflict occurs, the embodiments in the present disclosure and the features in the embodiments may be mutually combined. The foregoing descriptions are merely specific implementations of the present disclosure, but are not intended to limit the protection scope of the present disclosure. Any variation or replacement readily figured out by a person skilled in the art within the technical scope disclosed in the present disclosure shall fall within the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.
, Claims:I/We Claim:
1. A microbial activity monitoring and irrigation system (100) for soil, the monitoring and irrigation system (100) comprising:
a user interface (102) integrated with a user device (104), the user interface (102) configured to acquire input commands related to soil monitoring and irrigation management;
a plurality of wireless sensor probes (106) inserted within the soil, connected to the user interface (102) via a communication unit (140), the wireless sensor probes (106) configured to monitor microbial activity within the soil;
an irrigation unit (108) integrated with the system (100) for irrigating the soil as per requirement;
a communication network (110) configured to provide bidirectional data transmission within the system (100);
a processing unit (112) connected to the plurality of wireless sensor probes (106) and the irrigation unit (108)via the communication network (110), the processing unit (112) configured to process real-time data for microbial activity monitoring and irrigation, wherein the processing unit (112) further comprises;
an input module (116) configured to receive real-time data from the plurality of wireless sensor probes (106);
a pre-processing module (118) configured to pre-process received data into machine readable format for further analysis;
a monitoring module (122) configured to receive and process signals from the plurality of wireless sensor probes (106) to compute a Microbial Activity Index (MAI) for quantifying soil biological activity;
a comparison module (124) configured to compare the determined Microbial Activity Index (MAI) against a predefined threshold index to evaluate soil biological status and generate control signals for optimizing irrigation management;
a prediction module (126) configured to analyse soil biological status and forecast irrigation requirements to determine an optimized water application volume for improving microbial stability and enhancing soil fertility;
an irrigation control module (128) configured to regulate operation of the irrigation unit (108) in accordance with the predicted irrigation requirement to maintain optimal soil moisture balance;
an alert generation module (134) configured to generate and transmit real-time notifications related to microbial activity deviations and irrigation parameters to provide timely user intervention;
an output module (138) configured to transmit processed data to the user interface (102) for real-time monitoring, analysis, and informed irrigation decision-making;
2. The monitoring and irrigation system (100) as claimed in claim 1, wherein the system (100) further comprises a cloud database (114) configured to securely store, manage, and transmit retrieved input data for subsequent operations.
3. The system (100) as claimed in claim 1, wherein each of the wireless sensor probes (106) further comprises a oxygen (O2) sensor to monitor the oxygen concentration within the soil, a carbon dioxide (CO2) sensor to monitor carbon dioxide concentration, a electrochemical sensor to detect the presence of metabolic byproducts within the soil, a moisture sensor to detect the amount of moisture present within the soil, indicative of microbial respiration.
4. The system (100) as claimed in claim 1, wherein the user interface (102) is further configured to acquire key soil parameters including soil moisture level, temperature, microbial activity data, irrigation preferences, and user-defined irrigation control inputs.
5. The system (100) as claimed in claim 1, wherein the user interface (102) further comprises a chatbot (136) configured to interact with users by providing real-time soil health status, microbial activity insights, irrigation recommendations, assisting in data entry, retrieving historical soil records, and explaining irrigation decisions.
6. The system (100) as claimed in claim 1, wherein the system (100) includes a solar energy-harvesting unit configured to generate and store electrical power for operating the system (100) for providing continuous operation.
7. The system (100) as claimed in claim 1, wherein the processing unit (112) further comprises a training and testing module (130) configured to partition processed sensor data into training and testing datasets and iteratively train and refine a machine learning model to improve prediction accuracy for irrigation management.
8. The system (100) claimed in claim 1, wherein the processing unit (112) further comprises a data logging module (132) configured to organize and store input data from the wireless sensor probes (106) and user interface (102) into structured classifications for efficient analysis, historical tracking, and irrigation decision support.
9. The system (100) as claimed in claim 1, wherein the irrigation unit (108) comprises a pump assembly, a network of distribution pipelines, and a plurality of controllable valves configured to deliver water to the soil in accordance with control signals generated by the irrigation control module (128).
10. A method (400) for making a storage bag (100), the method (400) comprising:
acquiring soil monitoring and irrigation-related inputs via a user interface (102) integrated with a user device (104);
transmitting data between several components of the system (100) via a communication network (110);
processing received sensor data and user inputs to evaluate soil biological status via a processing unit (112) comprising several modules;
receiving input commands from the user interface (102) via an input module (116);
pre-processing collected sensor data by filtering noise, normalizing sensor values, and converting the data into a machine-readable format via a pre-processing module (118);
detecting microbial activities within soil via the wireless sensor probes (106);
monitoring a Microbial Activity Index (MAI) to quantify soil biological activity via a monitoring module (122);
comparing the determined Microbial Activity Index (MAI) with a predefined threshold index to evaluate the soil biological condition via a comparison module (124);
predicting an optimized irrigation requirement based on the evaluated soil biological status via a prediction module (126);
controlling operation of an irrigation unit (108) to deliver water to the soil according to the predicted irrigation requirement via an irrigation control module (128);
generating real-time alerts when deviations in microbial activity and irrigation parameters are detected via an alert generation module (134);
logging input data into a cloud database (114) in a structured classification via a data logging module (132);
separating processed sensor data into training and testing datasets via a training and testing module (130); and
transmitting processed soil condition data, irrigation decisions, and system (100) alerts to the user interface (102) via an output module (138).