AU2021106981A4 - A smart agriculture system with farm and water bodies managing robotic assembly using machine learning. - Google Patents

Abstract

: A smart agriculture system with farm and water bodies managing robotic assembly using machine learning. The invention describes the machine learning-based intelligent agriculture management system to control and monitor various factors of the agricultural farm to obtain the worthy output. The system has multiple sensor assembly arranges across the field and water bodies to identify the quality of the soil and water. The system performs the weeding process in case it identifies any weed growing with the healthy crop and it supplies precision-based pesticide supply when and where it identifies pests. It has a controlled feeding of water and fertilizer in each row based on the requirement analysis. The robotic modules monitors and analyses the water bodies near the farm to identify contamination if any and has a mechanism to clean the water bodies of oil and accumulated growth of algae and other plants which decrease the water quality. The robotic assembly also protects the farm against loitering and trespassing animal. For, (Applicant) Vidhyadhar Prakash Shendge Kishor Prakash Shendge Page 1 of 5 Applicant Vidhyadhar Prakash Shendge Kishor Prakash Shendge External Farm Information Commodity External Measure Source Maviet information Condibons Pricing Source on Farm System Sensor Devi-ce Sensor External Sourc Data Data External Measure Source Conmions'i. Data on Farm Receives sensor data and r External source data System# S eSor Pre-processes data Device+ Creates models Sensor Saves models Data Measure Conditions External Sensor on Farm Source Device . Data Sensor Data Farmers( Agronomists External Sensor Capture Information Sate ht ~ Device iae/Suc . Uv.. Video FIGURE - 1 For, (Applicant) Vidhyadhar Prakash Shendge Kishor Prakash Shendge

Description

Page 1 of 5

Applicant Vidhyadhar Prakash Shendge Kishor Prakash Shendge

External Farm Information Commodity External Measure Source Maviet information Condibons Pricing Source on Farm System

Sensor Devi-ce Sensor External Sourc Data Data External Measure Source Conmions'i. Data on Farm Receives sensor data and r External source data System# SeSor Pre-processes data Device+ Creates models

Sensor Saves models Data Measure Conditions External Sensor on Farm Source Device . Data Sensor Data Farmers( Agronomists External Sensor Capture Information Sate ht ~ Device iae/Suc . Uv.. Video

FIGURE - 1

For, (Applicant)

Vidhyadhar Prakash Shendge

Kishor Prakash Shendge

TITLE A smart agriculture system with farm and water bodies managing robotic assembly using machine learning.

FIELD OF INVENTION

[00011 This invention relates to the field of electronic engineering and the computer sciences more particularly an agriculture management system for monitoring controlling various factors of the agricultural farm to obtain the worthy output.

[0002] Here the system is designed with multiple robotic systems to monitor the soil and watering requirements required for the growth of healthy plants. It has been designed with the intelligence to identify the plant and pests which can harm the plant and the mechanism to control the watering system and fertilizer feeding system after receiving the calculated data from the sensor assembly arranged on the ground.

PRIOR ART AND PROBLEM TO BE SOLVED

[0003] In modern agricultural industries, accuracy is essential. Accurate record keeping, automated mapping, and precision farming techniques have all become crucial factors in the challenge to improve overall crops yields and comply with the ever-increasing number of environmental regulations. The accurate application of herbicides, pesticides and fertilizers is an essential component of modem precision farming methodologies. Whether such applications are performed by aerial or terrestrial techniques, advanced tools that provide highly accurate navigation and guidance information for operators have become a requirement. The success of growers depends upon an adequate supply of water (for example, rainfall) and other agricultural inputs for raising crops. The cost of providing irrigation or other agricultural inputs to crops is based on the quantity, frequency and rate of application of the agricultural input to a field. Accordingly, there is a need for providing low cost and accurate agricultural management parameters to growers to reduce or optimally allocate agricultural inputs (for example, water consumption and irrigation expenses) to the extent practical. A farmer's main inventory is the crop in the field. Managing that inventory requires knowledge about that inventory such as the count, size, colour, etc. of the crop on each tree, bush, or vine. To date, farmers estimate these parameters from relatively small samples taken by the manual observation that are prone to errors when projecting parameters of the entire crop. Because of the time, cost, and effort required to do these estimates, farmers often do not even perform these estimates. Satellite imagery has recently enabled macro-level estimates of some of these crop parameters such as tree vigour, crop ripeness by colour, or the presence of certain diseases. While this is useful information, it does not provide data at the individual tree/bush/vine level. For at least the reasons detailed in this section, there is a need for an agricultural robot system and method. Agriculture is a key sector of the Indian economy that deserves very good technical support which can be rendered through Artificial Intelligence. Stress associated with, such as climate change, nutrient deficiencies, weed, insect and fungal infestations, water availability and q should be identified well in advances as to provide an opportunity for the farmers to mitigate.

[0004] To resolve the above problem here a system is designed with robotic system assembly to monitor and take care that each of the facilities required for the growth of healthy crops is of good quality. Here the soil, water, fertilizer every parameter necessary is well monitored and it has a robotic system to provide quality analysis of the soil and a robotic system to provide a quality assessment of the water bodies used to pump water into the farms. The Machine learning based control and assistance assure that all the data received is controlled and processed and the farm is nourished based on the requirement alone without any possible overfeeding.

THE OBJECTIVES OF THE INVENTION:

[00051 Agriculture is one industry with traditionally low-profit margins and high manual labour costs. In particular, harvesting can be expensive. For some crops, such as tree fruit, harvesting labour represents the growers' single largest expense, up to % of total crop cost. Increasing labour costs and labour shortages threaten the economic viability of many farms. Therefore, replacing manual labour with robots would be extremely beneficial for harvesting. Additional benefits could be obtained through automating other tasks currently done manually such as pruning, culling, thinning, spraying, weeding, measuring and managing crops.

[0006] It has already been proposed where GPS controlled automated tractors and combines already operate in wheat and other grain fields. Automated harvesters exist that can blindly harvest fruit by causing the fruit to drop from a plant into a collection device. For example, industries make equipment that shakes oranges, grapes, raspberries, blueberries, etc. off plants. These harvesting approaches have wide-scale applicability but do not apply to the harvesting of all crops.

[0007] The principal objective of the invention is the machine learning-based intelligent agriculture management system to control and monitor various factors of the agricultural farm to obtain the worthy output.

[0008] Another objective of the invention is that agricultural soil, water and the regular fertilization system needs are kept in check to identify if the soil has enough moisture, is of good quality and the water bodies from which the water is being pumped into the farm is maintained to keep it hazard free from any form of contamination that can damage the soil and plant.

[0009] The further objective of the invention is that the system performs the weeding process in case it identifies any weed growing with the healthy crop and it supplies precision-based pesticide supply when and where it identifies pests. It is provided with the intelligence to identify the plant and pests which can harm the plant and to not irritate the pest like ant or butterfly which are not harmful for the cultivation.

[0010] The further objective of the invention is a controlled feeding of water and fertilizer in each row. In addition, the soil contamination is tested if while rotation or during any addition if the concentration of harmful matter is identifying like mercury or lack of nitrogen it will immediately raise an alarm so proper care can be taken. The soil quality is continuously measured using the machine learning mechanism helped to identify the possible product crop that can be grown.

[0011] The further objective of the invention is that it has robotic modules to monitor the water bodies near the farm. It performs continuous monitoring of the health and purity of the water body and it has been designed to clean the water bodies of oil and accumulated growth of algae and other plants which decrease the water quality.

[00121 The further objective of the invention is to provide aquatic life monitoring to get enough data regarding the health of the water body and once the water is assured to be of good quality, will only the robotic device start the water pumping process for irrigation.

[0013] The further objective of the invention is to protect the farm against loitering and trespassing animal. The robotic devices scare the animals far away from the farm making the entire management autonomous and with a predictable outcome of the harvest. It can keep in check the climatic condition to control the sheds and shades to protect the harvest against bad climate.

SUMMARY OF THE INVENTION

[0014] The ability to monitor and control the amount of water, chemicals and/or nutrients (applicants) applied to an agricultural field has increased the number of farmable acres in the world and increases the likelihood of a profitable crop yield. Known irrigation systems typically include a control device with a user interface allowing the operator to monitor and control one or more functions or operations of the irrigation system. Through the use of the user interface, operators can control and monitor numerous aspects of the irrigation system and the growing environment. Further, operators can receive significant environmental and growth data from local and remote sensors. Despite the significant amounts of data and control available to operators, present systems do not allow operators to model or otherwise use most of the data or control elements at their disposal. Instead, operators are limited to using intuition and snapshots of available data streams to make adjustments to their irrigation systems. Accordingly, despite the large amounts of data created, the decision making process for growers has not significantly changed in several decades. So here an autonomously controlled agriculture management system is designed that is capable of controlling and monitoring farm parameters which can help to produce healthy worthy crops. Apart from the field management, it identifies contamination in the soil and the water which is being fed into the farm. It keeps track of the fertilization and pesticide need sonly to the quantity required reducing overfeeding. The water bodies near the farm are monitored and regularly cleaned of the algae or the contaminations like oil, to keep it pure for agricultural use. The data obtained is analysed and the system is programmed with a machine-learning algorithm to make it smart to take an autonomous decision, to protect and control various apparatus in the farm. The farm is also defended against trespassing f any kind thus providing a complete robotized management of the farm.

DETAILED DESCRIPTION OF THE INVENTION

[00151 While the present invention is described herein by way of example, using various embodiments and illustrative drawings, those skilled in the art will recognize that the invention is neither intended to be limited to the embodiment of drawing or drawings described nor designed to represent the scale of the various components. Further, some components that may form a part of the invention may not be illustrated with specific figures, for ease of illustration, and such omissions do not limit the embodiment outlined in any way. The drawings and detailed description of it are not intended to restrict the invention to the form disclosed, but on the contrary, the invention covers all modifications, equivalents, and alternatives falling within the spirit and scope of the present invention as defined by the appended claims. The headings are used for organizational purposes only and are not meant to limit the scope of the description or the claims. As used throughout this specification, the word "may" be used in a permissive sense, rather than the mandatory sense.

[00161 Further, the words "an" or "a" mean "at least one" and the word "plurality" means one or more unless otherwise mentioned. Furthermore, the terminology and phraseology used herein is solely used for descriptive purposes and should not be construed as limiting in scope. Language such as "including," "comprising," "having," "containing," or "involving," and variations thereof, is intended to be broad and encompass the subject matter listed thereafter, equivalents and any additional subject matter not recited, and is not supposed to exclude any other additives, components, integers or steps. Likewise, the term "comprising" is considered synonymous with the terms "including" or "containing" for applicable legal purposes. Any discussion of documents acts, materials, devices, articles and the like are included in the specification solely to provide a context for the present invention.

[0017] In this disclosure, whenever an element or a group of elements is preceded with the transitional phrase "comprising", it is also understood that it contemplates the same element or group of elements with transitional phrases "consisting essentially of, "consisting", "selected from the group comprising", "including", or "is" preceding the recitation of the element or group of elements and vice versa.

[0018] Before explaining at least one embodiment of the invention in detail, it is to be understood that the present invention is not limited in its application to the details outlined in the following description or exemplified by the examples. The invention is capable of other embodiments or of being practised or carried out in various ways. Also, it is to be understood that the phraseology and terminology employed herein is for description and should not be regarded as limiting.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention belongs. Besides, the descriptions, materials, methods, and examples are illustrative only and not intended to be limiting. Methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention.

[0020] The present invention consists of a smart central system controlled multi robotic system to monitor the soil and watering requirements required for the growth of healthy plants. It has been designed with the intelligence to identify the plant and pests which can harm the plant and the mechanism to control the watering system and fertilizer feeding system after receiving the calculated data from the sensor assembly arranged on the ground.

[00211 The centrally controlled system receives the data from the variety of data sources as a corpus of data may pre-process the corpus of data to create training data, and may, through the use of machine learning, create one or more models that may be used to identify alerts relating to crops and recommended courses of action. Examples of alerts that may be identified include equipment malfunctions, crops that have patterns of disease or insect infestation, crops that require irrigation, etc. Examples of recommended courses of action may include, a predicted the best time to harvest a crop, a predicted the best time to sell a crop, the quantity of the crop to sell, when to purchase additional insurance coverage and the amount to purchase, when to water a crop, the quantity of water to use in watering a crop, when to use chemicals (example, fungicides) on a crop, the number of chemicals to use, when to schedule a worker to perform a particular action, when to schedule a company to repair or perform maintenance on a piece of equipment, etc. The precision agriculture system may also provide, concerning the identified alerts and/or the recommended courses of action, the financial impact of taking a recommended course of action and/or the financial impact of not taking a recommended course of action.

[00221 This arrangement has a large array of sensor assemblies to obtain vast data to perform precision farming using machine learning. Sensor devices include one or more devices for obtaining sensor-related information. For example, sensor device may include a camera (example, a visual spectrum imaging camera, an infrared or near infrared imaging camera, a multispectral imaging camera, a hyperspectral imaging camera, a thermal imaging camera, a laser mapping imagery camera, etc.), a sonar device capable of generating sonar-generated mapping imagery, a sensor capable of detecting precipitation, a sensor capable of detecting sunshine, a sensor capable of detecting relative humidity, a sensor capable of detecting atmospheric pressure, a sensor capable of detecting temperature above ground, a sensor capable of detecting temperature at one or more depths below ground, a sensor capable of detecting wind direction, a sensor capable of detecting wind speed, a sensor capable of detecting rainfall, a sensor capable of detecting irrigation flow, a sensor capable of detecting soil moisture, a sensor capable of detecting soil salinity, a sensor capable of detecting soil density, a sensor capable of detecting sap flow, a sensor capable of detecting equipment operating parameters, a sensor capable of detecting a silo fill level, a sensor capable of detecting a truck fill level, and/or any other sensor that would aid in making operational farming decisions. In some implementations, the sensor device may include or be attached to an unmanned aerial vehicle (UAV), an item of farming equipment (example, a tractor, an irrigation system, or the like), a tower (example, a cell tower or the like), or another type of device/vehicle.

[00231 The farming device may include one or more devices that provide a service at a farm. The farming device may receive information from the central system and perform an action based on receiving the information. For example, in the situation where the farming device is an irrigation system, the irrigation system may receive information from the system and to water a particular portion of a plot of the farm for a period based on the received information.

[00241 To receive the soil topography, a land-based robotic system is designed that is equipped with, pushing cone penetrometer (CPT) probes or other invasive sensors into the soil along a selected path, either vertical or angled. These probes contain sensors that are responsive to various soil properties. The signals from such sensors are relayed electrically or wirelessly up to the robotic system for logging and analysis. Penetrometer sensors can be used to measure or derive soil compaction, grain size, colour, organic matter content, moisture, temperature and resistivity, as well as other chemical and physical properties. Sensors may include electromagnetic and ground penetrating radar sensors, for example, capable of detecting subsurface structures such as clay lenses and inter-layer boundaries. A data acquisition system onboard vehicle collects data from deployed sensors and, with data from in-ground sensors correlated with depth as determined from a depth gauge, and all data correlated with a geographic position as determined by an on-board global positioning system (GPS). The on-board data acquisition system is also capable of integrating data c collected from sensors with pre-existing data for the site, and/or relaying raw or processed data off-site via a mobile telecommunications link. These sensors can include, among others, a miniature light source and receiver that together operate as a video camera to provide digital images of the soil surrounding the probe Such digital images can be particularly useful for subjective evaluation by skilled geologists thousands of miles from the test site, even before the probe is removed from the ground. It is also recommended that a full in situ video log be taken in each critical soil management zone at the end of the mapping sequence, for future reference. The soil is continuously monitored to predict the best crop that can be harvested in the sol for worthy results.

[00251 The robotic device monitoring the farm is designed to track the soil quality and the requirement along with identifying pests and weeds causing harm to the crops. It can detect and identify pests and send an alert to a computing device associated The pest detector module in the system includes one or more sensors, such as, for example, a motion sensor, an imaging sensor (example, a camera), an audio transducer (example, microphone), a structured light sensor, an ultrasound sensor, an infrared imaging sensor, a temperature (example, a thermistor) sensor, an ultrasonic sensor, a capacitive sensor, a micropower impulse radar sensor, Structured light involves projecting a known pattern (example, a grid or horizontal bars) of light on to an area (example, detection zone). How the light deforms when striking the area enables a vision system (for example, imaging sensor(s) and software) to determine the depth and surface information associated with a pest in the area. The pest detector may have one or more sensors that monitor a particular area (example, detection zone) or a set of (example, one or more) areas. When a sensor (for example, motion detector, infrared imaging sensor, or the like) detects motion associated with a potential pest in the detection zone, sensor data, such as an image of the potential pest, may be captured. The pest detector may use the gathered data (for example, digital image, movement information, and the like) associated with the potential pest to determine whether the data indicates a pest and if so, identify the pest using a machine learning (ML) algorithm. The ML may be trained to recognize multiple types of pests and to ignore data indicative of humans or pets (for example, dogs and cats). In some cases, the type of pests that the ML can recognize may be based on the geographic region in which the pest detector is placed.

[00261 The robotic module may include bait and two small electrodes to lure and kill (for example, using electrocution) a small pest, such as a mosquito, a fly, an ant, or small cockroach, or another type of pest. The detector models may include a detector with a swivelling A/C plug to enable a user to position the detection area to be below the detector. The data gathered by each detector (for example, pest-related data) may be sent to a server (for example, a cloud-based server). The server may thus receive data from multiple detectors in each of multiple locations. The location in the farm where the pest has been identified, the pesticide can be sprayed only to that section without contaminating the entire farm. In addition, the robotic system is designed to place the electrified mesh. When the pest touches the electrified mesh, the pest may be killed (example, electrocuted) by supplying power (example, voltage and current) to the electrified mesh. In some cases, the electrified mesh may be provided power without regard to whether a pest is detected. In other cases, the plugin( may include a sensor, such as a motion sensor. When the motion sensor detects movement, the detector may supply power to the electrified mesh. When the motion sensor no longer detects movement, the detector may stop supplying power to the electrified mesh. In some cases, the bait may be used without the electrified mesh to attract pests to come near the detector to enable the detector to gather sensor data from the sensors. The mechanism used helps to reduce the overfeeding of pesticides and protects the farm against contamination.

[00271 The other parameter that is well controlled by the central system is irrigation. The farm is provided with a controlled mechanism of water feeding. The robotic system is responsible to regulate the water across the farm. The robotic system is connected wirelessly to the irrigation system across the farm and it is connected to a water or well source. The irrigation system includes transducers, which are provided to control and regulate water pressure, as well as drive units, which are preferably programmed to monitor and control portions of the irrigation unit drive system. It has a flow meter for monitoring water flow in the system. The robotic system received the sensor data including the soil moisture level. The sensors further include optics to allow for the detection of crop type, stage of growth, health, presence of disease, rate of growth and the like. One or more direct sensors are attached to a plant to provide direct readings of plant health and status. Additionally, one or more direct soil sensors are used to generate soil moisture, nutrient content or other soil-related data. soil sensors may record data related to a variety of soil properties including soil texture, salinity, organic matter levels, nitrate levels, soil pH, and clay levels. The robotic monitoring system further includes a climate station or the like which can measure weather features such as humidity, barometric pressure, precipitation, temperature, incoming solar radiation, wind speed and the like.

[00281 The irrigation system set up in the farm field is attached/linked to the robotic device to control the movement of the irrigation system. The robotic system directly transmits and receive data from the various span sensors to a machine learning module equipped in the central management system.

[00291 Water sources may contain additional sources such as, for example, without limitation, fertilizer, herbicide, insecticide, fungicide, plant food, and other substances used in plant care and maintenance. As used herein, watering solution refers to water and/or other substances that may be applied to plants, The robotic system is equipped with the knowledge base to control and perform an action for the field. It contains information, such as, without limitation, plant species and varieties located in the operating environment, information about the water needs, growth stages, and life cycles of the plant species and varieties located in the operating environment, current weather for the operating environment, weather history for the operating environment, specific environmental features of the operating environment that affect the working of the robotic system. It is designed to monitor the water supplier. The irrigation unit includes a water supplier connector, piping system, and watering solution application system. Water supplier connector may allow for the connection of an on-board tank, a towed tank, a hose, and/or any other suitable device for carrying watering solution. A hose may be any type of flexible tubing suitable for carrying watering solutions. Water supplier connectors may contain threads that mate with the threads commonly found at the end of a hose, for example. The water supplier connector may also include a rubber seal to prevent leakage. A piping system is several pipes used to convey watering solution from one location to another in a watering unit. A piping system may allow watering solution from a water source connected to a water supplier connector to flow to the water irrigation system. It includes a valve system and watering solution applicator.

[00301 A watering solution applicator may be any type of watering solution application device that includes a pressure system for forcing the watering solution through the piping system and out some openings of the watering solution applicator. As used herein, several openings refer to one or more openings. For example, a watering solution applicator may be, without limitation, a fixed pattern sprinkler, a spray head, a nozzle, an impact sprinkler, an oscillating sprinkler, a pulsating sprinkler, a spout, and any other type of opening that allows for the application of watering solution from a water supplier, such as a garden hose,

[00311 The sensor system is a high integrity perception system and maybe a set of sensors used to collect information about the environment around a robotic system. The information is sent to a central system to provide data in identifying how the robotic system should command the irrigation system to apply the watering solution, specifically providing data about the number of plants and current conditions in the operating environment.

[00321 The robotic system manages information collected by the sensors including soil moisture, water retention, and the actual amount of water applied. The actual water uses of an individual plant can be used by a processing system, such as a machine controller, to adjust the amount of water applied in future water use applications. It further contains information about the amount of water and/or other substances that should be applied to each plant. Other substances may be, for example, without limitation, fertilizer, plant food, pesticide, and the like.

[00331 The robotic system can operate effectively across a range of surface conditions created by different cultivation methods (example, no-till, low-till, strip-till, and conventional tillage), and on different soil types with different crops planted the previous year (that is, over a range of plant residue conditions). In addition, it can operate on soils that would be too wet for conventional equipment. Depending upon the soil type, soil moisture, and plant residue, various approaches can be used for applying fertilizer. The fertilizer can be applied substantially between two rows of planted crops or can be sprayed across the field. The Capacitive sensors embedded in the front of the robot's shell (the obstacle sensors) detect tall objects, similar sensors under the shell (the weed sensors) detect any plant short enough to be overrun by the robot. When the robot detects a tall object, it turns away and chooses another path. But, when a short plant activates the under-shell sensor, the robot switches on the weed cutting mechanism. The robot may then wait a short time and/or move a short distance.

[00341 In addition to the irrigation monitoring, it is necessary to identify that the water source, from which the water is being pumped into the farm is clean and well maintained and is free of any form of contamination. Contaminated water will contaminate the soil thus shredding it of its fertility and poisoning the plants. The central system has a floating robotic system linked to it to manage and control the water bodies. The floating robotic system is anchored into the water body and is coupled to the filter apparatus with a flexible conduit. Here the power is applied to the pump in the floating robotic system and water and solid debris are sucked into the vortex chamber of the robot. The solid debris is ground or chopped fine by the pump and the water and reduced solids mixture is pumped through the conduit to the filter apparatus. The reduced debris is separated from the water by the screen in the filter and is either deposited in the removable tray or allowed to fall onto a compost heap. The water from the filter is optionally aerated and returned to the pond/water body.

[00351 The floating robotic system further consists of a Sterilizing Circulator that is an ultrasonic horn tuned to a plurality of frequencies that effectively kill microbial cells, such as water-borne pathogens and undesirable algae. The effective frequency is not the same for all organisms. It further encourages bacterial growth, not kill it. There is a balance because some organisms are desirable and some, like pathogens and malodor-producing bacteria, are unwanted. Particularly, algae are usually unwanted because they are measured as suspended solids, a regulated result. The sterilizing unit emits ionizing radiation such as ultraviolet (UV) wavelengths selected for their lethality to water-borne pathogens and undesirable algae. It is also effective at dissociating certain chemical pollutants. This effect is especially obtained with UV and other ionizing radiation.

[00361 The robotic system further has another circulator system that is adapted for generating microbubbles. The aeration process is supplemented by mounting an electric pump or air blower on a flotation device adjacent to the aerator, connecting the pump or blower to an appropriate type and size of line to carry the outgoing water or air to a water-activated venturi. Lines continue from venturi, via connections as required, to the aerator, where the diverter is pierced by a flanged pipe. An elbow or deflector is provided at the inner end of the flanged pipe to direct the flow of the water or air to mix with up flowing water within the intake tube and outward across the outflow lip, as indicated by arrows, and across the surface of the water. The result is to increase the dissolved oxygen content in the water to be treated. Once the water is identified to be good only then the land-based robotic system after coordinating with the aquatic robotic system will allow the irrigation system to pump the water onto the farm.

[00371 To protect the farm against predators each of the robotic devices is provided with a laser beam multi-irradiation means for irradiating a plurality of laser beams in a collective state to a space where birds and animals are to be prevented from entering, thereby forming a laser beam network in the space. It is characterized in the retina of the bird and animal and creates a distraction. It has been provided with a sound mechanism to make it feel like a presence of a human in the field to keep the animal or bird out of the field. The robotic system is equipped with apparatus that can be projected into the sky with a loud sound in case any trespassing is observed by the optical sensors ensuring that nothing enters the field. Notification of all the activities happening in the field is sent to a user device.

[0038] The user device may include a device capable of receiving, generating, storing, processing, and/or providing information, such as the information described herein. For example, user device 110 may include a computing device (e.g., a desktop computer, a laptop computer, a tablet computer, a handheld computer, a server, etc.), a mobile phone (e.g., a smartphone, a radiotelephone, etc.), or a similar device. In some implementations, the user device may receive information from and/or transmit information to a precision agriculture system In some implementations, the user device may include a Precision Agriculture

System (PAS) application that provides information (e.g., sensor information, weather information, aerial imagery, yield projections, financial information, etc.), alerts based on such information, and, if appropriate, action items (e.g., that allow the farmer to initiate automated systems and/or manual operations).

[00391 The communication interface may include a transceiver-like component (e.g., a transceiver, a separate receiver and transmitter, etc.) that enables the device to communicate with other devices, such as via a wired connection, a wireless connection, or a combination of wired and wireless connections. The communication interface may permit the device to receive information from another device and/or provide information to another device. For example, a communication interface may include an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, a radio frequency (RF) interface, a universal serial bus (USB) interface, a Wi-Fi interface, a cellular network interface, or the like.

[0040] The network may include one or more wired and/or wireless networks. For example, the network may include a cellular network (e.g., a long-term evolution (LTE) network, a 3G network, a code division multiple access (CDMA) network, etc.), a public land mobile network (PLMN), a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a telephone network (e.g., the Public Switched Telephone Network (PSTN)), a private network, an ad hoc network, an intranet, the Internet, a fibre optic-based network, a cloud computing network, and/or a combination of these or another type of network.

[0041] While there has been illustrated and described embodiments of the present invention, those of ordinary skill in the art, to be understood that various changes may be made to these embodiments without departing from the principles and spirit of the present invention, modifications, substitutions and modifications, the scope of the invention being indicated by the appended claims and their equivalents.

FIGURE DESCRIPTION

[0042] The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate an exemplary embodiment and, together with the description, explain the disclosed embodiment. In the figures, the left and rightmost digit(s) of a reference number identify the figure in which the reference number first appears. The same numbers are used throughout the figures to reference features and components. Some embodiments of the system and methods of an embodiment of the present subject matter are now described, by way of example only, and concerning the accompanying figures, in which:

[00431 Figure- 1 shows the block diagrammatic structure of all the components connected to the centralized system.

[0044] Figure - 2 shows the block structure of the land-based robotic system capable of sensing the soil parameters using a sampling mechanism.

[0045] Figure - 3 shows the flow diagram of the irrigation management module.

[0046] Figure - 4 illustrates the flow of the pest detection module.

[00471 Figure -5 shows the flow of the weed cutting mechanism in the robotic system.

Claims (9)

CLAIMS: I/We claim:

1. A machine learning based intelligent agriculture management system to control and monitor various factors of the agricultural farm to obtain worthy output consisting of; Soil Sampling module; Sensor assembly; Robotic devices; Power Supply; Irrigation system; Water Sampler; Weed cutting module; Pest analysis module; Algae cleaning module; Water filter module; Plant health analysis module;

2. The management system as claimed in claim - 1, consists of land based and water based robotic devices for autonomous control and management of agricultural soil, water and the regular fertilization system needs of the farm after the analysis of soil quality and water quality and the requirement of the farm.

3. The management system as claimed in claim - 1, performs the weeding process in case it identifies any weed growing with the healthy crop and it supplies precision based pesticide supply when and where it identifies pest.

4. The management system as claimed in claim - 1, provides controlled feeding of water and fertilizer in each row

5. The management system as claimed in claim - 1, robotic modules to monitor the water bodies near the farm before pumping to identify contamination if any, protecting the quality of soil and plants.

6. The management system as claimed in claim - 1, clean the water bodies of oil and accumulated growth of algae and other plants which decrease the water quality.

7. The management system as claimed in claim - 1, provide protection to the farm against loitering and trespassing animal using laser, sound-based mechanism to scare the animal away from the field automatically.

8. The management system as claimed in claim - 1, keep in check the climatic condition to control the sheds and shades to protect the harvest against bad climate.

9. The management system as claimed in claim - 1, provides immediate notification to the user for each analysis or action performed by the central system, robotic assembly or agricultural equipment.

For, (Applicant)

Vidhyadhar Prakash Shendge

Kishor Prakash Shendge

Page 1 of 5

Applicant 24 Aug 2021

Vidhyadhar Prakash Shendge Kishor Prakash Shendge 2021106981

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