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Smart IoT Irrigation System with Real-Time Growth Monitoring for Efficient Water Use and Enhanced Crop Yield

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Smart IoT Irrigation System with Real-Time Growth Monitoring for Efficient Water Use and Enhanced Crop Yield

ORDINARY APPLICATION

Published

date

Filed on 24 November 2024

Abstract

SMART IOT IRRIGATION SYSTEM WITH REAL-TIME GROWTH MONITORING FOR EFFICIENT WATER USE AND ENHANCED CROP YIELD The method for the development of conventional and smart irrigation technologies and discuss their effect on water savings, yield, and crop quality. Compared to open-loop systems that do not account for uncertainties, closed-loop irrigation control strategies are more effective. It is suggested that water use efficiency can be greatly increased by integrating soil-, plant-, and weather-based monitoring techniques in a modeling environment with model predictive control. In order to enhance irrigation scheduling in open field agricultural systems, this review will assist researchers and farmers in selecting the most effective irrigation monitoring and control method. Irrigation systems have been identified as a beneficial contributor to the development of optimized irrigation systems, which may improve the application of ongoing research and development aimed at improving cost-effectiveness and sustainable operations. The optical sensor-based system showed a better ability to assess crop and soil variability in the field than the on-site measurements. FIG.1

Patent Information

Application ID202441091502
Invention FieldMECHANICAL ENGINEERING
Date of Application24/11/2024
Publication Number48/2024

Inventors

NameAddressCountryNationality
Dr. Santhosh PoojaryAssistant Professor, Nitte (Deemed to be University) NMAM Institute of Technology Nitte, 574110, Karkala Udupi District, KarnatakaIndiaIndia

Applicants

NameAddressCountryNationality
Dr. Santhosh PoojaryAssistant Professor, Nitte (Deemed to be University) NMAM Institute of Technology Nitte, 574110, Karkala Udupi District, KarnatakaIndiaIndia

Specification

Description:SMART IOT IRRIGATION SYSTEM WITH REAL-TIME GROWTH MONITORING FOR EFFICIENT WATER USE AND ENHANCED CROP YIELD

Technical Field
[0001] The embodiments herein generally relate to a method for smart IoT irrigation system with real-time growth monitoring for efficient water use and enhanced crop yield.
Description of the Related Art
[0002] The water productivity improves, the Food and Agricultural Organization (FAO) predicts that by 2050, irrigated food production will have increased by more than 50%, requiring a 10% increase in water abstracted for agriculture (FAO, 2020b). Since the amount of land used for food production does not increase, agricultural cropping systems must make effective use of the water and land resources at their disposal in order to feed the world's population in the future. Therefore, it is crucial to comprehend the mechanisms that can increase water use efficiency, lead to notable water savings, and increase yield. Agriculture is the backbone of the economy and a significant industry. For all nations, agriculture automation is a significant issue and a developing subject. The demand for food is rising along with the world's population, which is growing at a rapid pace. challenging for the agricultural sector to create methods and procedures that will enable them to completely meet the growing demands and specifications. Effective irrigation systems that conserve water offer different ways to deal with this issue. These programs ensure crop yields even in cases where irrigation water is insufficient because of the significantly increased water-use efficiency of crops. It has become very important due to the growing demand for food and shifting consumer preferences.
[0003] As the effects of climate change continue to cause water scarcity to vary globally in both space and time, researchers have turned their attention to water use efficiency. Farmers, irrigation engineers, and policymakers have had to reevaluate how water is used in agriculture due to competition from other economic sectors for the limited supply of water. It appears that in order to meet the demands of agricultural production, cutting-edge methods of water management and systems will have to be implemented in order to address the shrinking land base and water allocations. In order to ensure greater water use efficiency, precision agricultural technologies are essential. Using data-intensive techniques, smart irrigation is a new scientific field that aims to boost agricultural productivity while lessening its environmental impact. A greater understanding of the operation environment and the activities involved is made possible by the data generated by various sensors in modern agricultural operations. Farmers use uniform irrigation in conventional farm-scale irrigation, ignoring crop water requirements and field variability. A number of detrimental effects on the environment and the economy could result from over- or under-irrigation if sophisticated irrigation management is not used.
[0004] The spatiotemporal variation of soil properties and weather variables that impact crop evapotranspiration are not taken into account by conventional irrigation systems when applying irrigation water. As a result, the actual depth of irrigation water that plants receive varies spatially. While insufficient irrigation can cause plant stress, which could lower crop yield and quality, excessive irrigation water application causes fertilizer leaching, deep percolation, surface ponding, and runoff. Lack of field experience and the scarcity of land reservoirs were two of the main causes. Unirrigated land zones have developed as a result of the ongoing removal of water from the earth, which has caused water levels to drop.
SUMMARY
[0001] In view of the foregoing, an embodiment herein provides a method for smart IoT irrigation system with real-time growth monitoring for efficient water use and enhanced crop yield. In some embodiments, wherein the implementing an optimized irrigation schedule through a smart irrigation system requires sensors to monitor soil, plant, weather conditions. Irrigation control, on the other hand, deals with the distribution of inputs and the necessary modifications based on crop response in order to conserve irrigation water while reducing the impact of uncertainties and disturbances. An emerging method for automating irrigation systems and saving water is the SMART irrigation system, which improves performance. This method allows farmers to meet their demand with a newly adopted technique that conserves water for the irrigation process by adjusting irrigation based on actual soil and weather conditions. At the basin scale, precise measurement of the water amounts supplied to irrigators is crucial. IWUE is directly impacted by irrigation scheduling, which is the process of deciding how much and when to apply irrigation. The IWUE decreases when more water is applied than is required for the best plant uptake.
[0002] In some embodiments, wherein to the best of our knowledge, there don't seem to be many systematic literature reviews on the use of monitoring and control strategies for improving water use efficiency. The authors don't demonstrate how precision agriculture's water use efficiency can be monitored and controlled. By integrating irrigation control methods to increase water use efficiency with clever crop water use monitoring strategies, this review expands on previous research. Farmers can now further understand the precise condition of their field, including soil temperature, water requirements, weather, and much more, thanks to technologies like sensors, smartphone tools, and the Internet of Things (IoT). The Internet of Things (IoT) can be viewed as an expansion of the existing internet that encompasses all devices that are connected to the internet and have the ability to communicate with electronic devices, making them easy to use and manage. In order to make better irrigation decisions that could lead to significant water savings and increased yield, PI requires knowledge of irrigation systems, soil variation over time and space, soil structure and hydraulic properties, changing weather variables, crop phenology, and irrigation requirements. Smith et al. claim that by applying water precisely where it is needed, PI enables the timing, volume, and spatial distribution of water applications to optimize yield or WUE.
[0003] In some embodiments, wherein water use efficiency is directly impacted by irrigation scheduling, which determines when and how much water to apply to the field. A criterion to ascertain the irrigation requirement and strategy to prescribe the amount of water to be applied is used to estimate the amount of water to be applied. Farmers can better understand their crops, lessen their impact on the environment, and save resources by using sensors. Therefore, farmers have the chance to generate yields while utilizing fewer resources, like seeds, fertilizers, and water, by implementing SMART agriculture. This study intends to demonstrate how SMART irrigation, which makes use of sensory systems and the Internet of Things (IoT), contributes to the SDGs. Precision irrigation makes use of the ideas of artificial intelligence (AI) and optimization. On the one hand, artificial intelligence in irrigation refers to the ability to learn and/or make decisions based on data processing and reasoning in order to define and modify irrigation applications and prescriptions on the field.
[0004] These and other aspects of the embodiments herein will be better appreciated and understood when considered in conjunction with the following description and the accompanying drawings. It should be understood, however, that the following descriptions, while indicating preferred embodiments and numerous specific details thereof, are given by way of illustration and not of limitation. Many changes and modifications may be made within the scope of the embodiments herein without departing from the spirit thereof, and the embodiments herein include all such modifications.

BRIEF DESCRIPTION OF THE DRAWINGS
[0001] The embodiments herein will be better understood from the following detailed description with reference to the drawings, in which:
[0002] FIG. 1 illustrates a method for smart IoT irrigation system with real-time growth monitoring for efficient water use and enhanced crop yield according to an embodiment herein; and
[0003] FIG. 2 illustrates a method for SMART irrigation system according to an embodiment herein.
DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS
[0001] The embodiments herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting embodiments that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
[0002] FIG. 1 illustrates a method for smart IoT irrigation system with real-time growth monitoring for efficient water use and enhanced crop yield according to an embodiment herein. In some embodiments, it is important to keep an eye on certain elements that affect crop growth and development in order to increase water use efficiency. Using cutting-edge communication technologies, monitoring from the standpoint of smart irrigation also comprises gathering data in real-time on the condition of the soil, plants, and weather parameters in the cropped area. Plant development and growth are influenced by efficient and effective monitoring systems, which are also essential for designing an irrigation control system that maximizes food production while minimizing water loss. Using the Internet of Things (IoT) and wireless technology, monitoring in the specific context of precision irrigation involves gathering data that effectively reflects the current condition of the plants, soil, and weather in irrigation areas. ABM techniques that enable the representation of entity heterogeneity, roles, and interactions can be used to model dynamic and autonomous entities in crop fields and irrigation districts. Virtual irrigated systems can be created and utilized as virtual labs with ABM. When actual experiments are not possible, these labs serve as a substitute. The soil moisture distributions revealed clear spatiotemporal characteristics through real-time monitoring of the soil moisture data in the profile; for example, as the tomato grew, the soil moisture showed a ladder trend for 0-60 cm and a stable trend for 60-100 cm.
[0003] In some embodiments, the control strategies that precisely apply irrigation water must be implemented if irrigation is to be sustainable. In addition to applying the necessary amount of irrigation water for a predetermined amount of time, an irrigation controller helps to save labor costs and achieve high water, energy, and fertilizer efficiency. Water on-demand irrigation and suspended cycle irrigation are the two main soil moisture sensor-based systems. A suspended cycle is more akin to a conventional timer controller, which features start, stop, duration, and watering schedules. The distinction is that when the soil has sufficient moisture, the system will automatically halt the subsequent planned irrigation. Based on crop phenology, simulation models can be used to model how crops will react to irrigation management. By removing the need for laborious field experiments, these crop models present a chance to enhance precision irrigation techniques. The FAO created the Aqua Crop water model, which models how crop yield is affected by water. Because Aqua Crop was calibrated for multiple crops, crop yields could be calculated using varying sowing dates, soil types, climates, irrigation frequencies, and amounts. To carry out irrigation events in a greenhouse tomato cultivation experiment, an automated drip irrigation system comprising wireless moisture sensors, wireless control nodes, and a central irrigation controller was created. Compared with the previous irrigation decision schemes, the designed irrigation depth was determined at every irrigation event based on the dynamic irrigation depth estimated from real-time soil moisture data.
[0004] In some embodiments, in recent years, researchers have paid close attention to the need to increase the efficiency of water use in irrigated agriculture. According to reports, agriculture uses a lot of water, but spatiotemporal water scarcity indices are rising, leaving little to no water available for agricultural production. The coverage path planning algorithm, which uses environmental data and a map of static elements, could be used to improve irrigation robot navigation. The three primary layers of the robot's control system could be developed using the robot operating system. The first layer is responsible for reading sensor data, the second layer is responsible for communication, and the third layer is responsible for path planning and decision-making. Low-cost electronic devices can enhance agronomists' or farmers' interactions with crops, soil, and environments under the Internet of Things paradigm, while online software and processing power can yield useful data. When it comes to irrigation procedures, IoT-based soil and plant monitoring can enhance irrigation by saving water, which is valuable in some particular geographic areas.
[0005] FIG. 2 illustrates a method for SMART irrigation system according to an embodiment herein. In some embodiments, the various devices that make up IoT systems are positioned to carry out a wide range of tasks, including control, monitoring, detection, and action. These specific devices are further thought to have interfaces that allow connections to be made with other devices in order to send the necessary data. Additionally, the data collected by different sensors will typically be processed, and the outcomes will be applied to different actuators. To improve irrigation water use efficiency (WUE) and resolve conflicts in water distribution among users of a large irrigation district, an intelligent multiagent irrigation system was developed. The representation of group decision-making processes through the integration of ABM, crop modeling, and IoT is the work's contribution. The management of irrigation scheduling at the farm and basin scales is the strategy we suggest. An intelligent irrigation agent keeps an eye on each field.
[0006] In some embodiments, there are many potential applications for IoT techniques incorporated into irrigation systems in agriculture and food production. Cost, autonomous operation, portability, low maintenance, efficacy, robust architecture, and reliability are just a few of the many IoT-related aspects of smart irrigation that require more attention. It is projected that agriculture will transform into a dynamic sector once integrated systems acknowledge the potential of big data and artificial intelligence. The system included a number of virtual (software) and real (robotic) agents. In order to meet the crop water requirements based on site-specific factors, irrigation agents are responsible for establishing and implementing an irrigation schedule for each zone or parcel during the season. A negotiation protocol is created for the stakeholders to divide up the water in the event of a shortage.
[0007] In some embodiments, in an effort to reduce expenses and increase productivity, organizations in the agricultural sector and others engaged in irrigation operations worldwide have grown increasingly interested in implementing smart irrigation techniques. An instance that could be recognized is the case of Water Bit, an industrial company. The organization is a cutting-edge technology company that has partnered with AT&T, one of the biggest telecom companies globally, to offer its autonomous irrigation solution secure wireless connectivity, enabling local irrigation management and control. According to Jiménez et al., four actual intelligent irrigation systems ri-agents were used in the IIoTPIS. The measurement system (MS), application system (AS), and central station (CS) are integrated to create real intelligent agents. In a mesh network, up to nine sensor nodes could be linked to the central station; however, the number of management zones determines how many sensor nodes are installed.
, Claims:I/We Claim:
1. A method for smart IoT irrigation system with real-time growth monitoring for efficient water use and enhanced crop yield, wherein the method comprises;
optimizing water usage by reducing water wastage by delivering precise irrigation based on soil moisture, weather data, and plant growth stages;
monitoring plant health by continuously tracking crop growth and detecting anomalies through real-time sensors and imaging technology;
enhancing crop yields by improving crop production by maintaining ideal growth conditions through data-driven irrigation and monitoring;
minimizing resource waste by streamlining water, energy, and fertilizer use through automated decision-making and targeted delivery;
predicting growth patterns by leveraging real-time analytics to forecast crop development and identify potential challenges;
integrating advanced sensors by using IoT-enabled soil, temperature, and light sensors to gather actionable insights for better irrigation control;
enabling remote management by allowing farmers to monitor and adjust irrigation schedules through a smartphone or web-based interface, ensuring convenience and efficiency;
promoting sustainable agriculture by supporting eco-friendly farming practices by conserving water and maximizing yield with minimal environmental impact;
alerting farmers proactively by sending notifications on water levels, plant stress, and system anomalies for timely interventions; and
automating irrigation systems by utilizing ai-driven algorithms to automate water distribution, tailored to crop needs in real-time.
Dated this, 23rd November, 2024.

Signature

Documents

NameDate
202441091502-COMPLETE SPECIFICATION [24-11-2024(online)].pdf24/11/2024
202441091502-DECLARATION OF INVENTORSHIP (FORM 5) [24-11-2024(online)].pdf24/11/2024
202441091502-DRAWINGS [24-11-2024(online)].pdf24/11/2024
202441091502-FORM 1 [24-11-2024(online)].pdf24/11/2024
202441091502-FORM-9 [24-11-2024(online)].pdf24/11/2024
202441091502-POWER OF AUTHORITY [24-11-2024(online)].pdf24/11/2024
202441091502-REQUEST FOR EARLY PUBLICATION(FORM-9) [24-11-2024(online)].pdf24/11/2024

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