VISION-BASED EDGE TECHNOLOGY FOR RICE SACK COUNTING AND MONITORING IN AGRICULTURAL FIELDS USING RICE REAPER

Abstract

A system of vision-based edge technology for rice sack counting and monitoring in agricultural fields using rice reaper comprises TCNVET_RSCMote (100), which has a BeagleBone Processor Board (107), Camera (103), GSM Modem (101), Neural Stick (102), Proximity Sensor (106), Buzzer (105), and Power Supply (104), is used to automate the precise counting and monitoring of rice sacks during harvesting, it also integrates real-time cloud connectivity for instant updates and provides operators with data-driven insights for improved decision-making the central processing unit of TCNVET_RSCMote, the BeagleBone Processor Board, enables effective coordination and communication to enable real-time AI and ML algorithms for precise rice sack counting during the harvesting process.

Specification

Description:FIELD OF THE INVENTION
This invention relates to vision-based edge technology for rice sack counting and monitoring in agricultural fields using rice reaper.
BACKGROUND OF THE INVENTION
This innovative vision-based technology provides an advanced solution for automated rice sack counting and monitoring during the harvesting process, revolutionizing the agricultural industry. The technology analyzes live camera feeds from the field using cutting-edge AI and ML algorithms to exactly calculate how many sacks the Rice Reaper filled. Real-time cloud connectivity ensures that operators may easily access a personalized mobile dashboard with real-time data and alarms.
During the harvesting process, the traditional method of physically counting and monitoring rice bags poses significant hurdles to timely, accurate, and efficient decision-making. Counting methods that require a lot of work can be inaccurate and lead to inconsistent data being collected. Moreover, the lack of up-to-date data hinders the capacity to immediately resolve problems or streamline the harvesting procedure.
CN206196362U: The utility model discloses a kind of husk separate type rice harvester, including harvest mechanism, conveyer belt, workbench, frame, threshing chamber, vertical helical feed road, No. two swash plates, flow distribution plate, Rose Box and horizontal helical feed road, harvest mechanism includes carrier chain, a number motor and cutter, conveyer belt is provided with below carrier chain, workbench is provided with above conveyer belt, lifting connecting rod is hinged with workbench, lifting connecting rod is connected with harvest mechanism, workbench is fixedly mounted on the left end upper surface of frame by column, the upper surface of frame is further fixedly arranged on separator box, the inside of separator box is sequentially provided with threshing chamber from top to bottom, No. two swash plates, filter, Rose Box and horizontal helical feed road, wherein threshing chamber is connected with conveyer belt.The utility model simple structure, reasonable in design, rice harvesting paddy rice shelling effect is good, while the impurity contained in grain has further been separated, with practical value very high.
RESEARCH GAP: A vision based edge technology for Rice Sack Counting and Monitoring in Agricultural Fields using Rice Reaper is the novelty of the system.
CN107736125A: The present invention relates to agricultural technology field, in particular a kind of rice harvester cutter device, including cutting box, the bottom of cutting box is provided with firm banking, conveyer belt is installed on the left of firm banking, the inner upper of cutting box is provided with supporting plate, one end of supporting plate is fixedly connected with cutting box, the right side of cutting box is provided with feeding mouth, the left side of cutting box is provided with discharging opening, the inside of cutting box is sequentially provided with the first cutting mechanism from right to left, second cutting mechanism, 3rd cutting mechanism, dust collection chamber, the attachment structure that the present invention passes through uniqueness, make rice after cutting box is entered, cut by the combination of three layers of cutting mechanism, can efficiently separate stalk and spike of rice, improve the Threshing of harvester, stalk is repeatedly cut inside cutting box, the big cutting efficiency for improving harvester;And by the dust collection chamber of setting, it can effectively prevent machine breakdown caused by using rear stalk dust obstruction harvester internal part for a long time.
RESEARCH GAP: A vision based edge technology for Rice Sack Counting and Monitoring in Agricultural Fields using Rice Reaper is the novelty of the system.
SUMMARY OF THE INVENTION
This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention.
This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.
To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
The vision-based technology for rice sack counting and monitoring is made possible by the TCNVET_RSCMote, which functions by integrating its components in a smooth manner. As the system's central processing unit and coordinator of other components' actions to guarantee a smooth workflow, the BeagleBone Processor Board starts the process. A live feed of the agricultural field throughout the rice harvest process is captured by a strategically placed camera, which forms the basis of this innovation. The Neural Stick is equipped with sophisticated AI and ML algorithms that process visual data in order to identify and tally the sacks that the Rice Reaper has filled. This automation technique is incredibly precise and effective. The addition of a GSM modem improves real-time capabilities by allowing communication over GSM networks and allowing the TCNVET_RSCMote to deliver alerts and updates in real time.
BRIEF DESCRIPTION OF THE DRAWINGS
The illustrated embodiments of the subject matter will be understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and methods that are consistent with the subject matter as claimed herein, wherein:
FIGURE 1: SYSTEM ARCHITECTURE
The figures depict embodiments of the present subject matter for the purposes of illustration only. A person skilled in the art will easily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.
DETAILED DESCRIPTION OF THE INVENTION
The detailed description of various exemplary embodiments of the disclosure is described herein with reference to the accompanying drawings. It should be noted that the embodiments are described herein in such details as to clearly communicate the disclosure. However, the amount of details provided herein 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 scope of the present disclosure as defined by the appended claims.
It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present disclosure. Moreover, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples, are intended to encompass equivalents thereof.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms "a"," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes" and/or "including," when used herein, specify the presence of stated features, integers, steps, operations, elements and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
In addition, the descriptions of "first", "second", "third", and the like in the present invention are used for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Thus, features defining "first" and "second" may include at least one of the features, either explicitly or implicitly.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, e.g., those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The vision-based technology for rice sack counting and monitoring is made possible by the TCNVET_RSCMote, which functions by integrating its components in a smooth manner. As the system's central processing unit and coordinator of other components' actions to guarantee a smooth workflow, the BeagleBone Processor Board starts the process. A live feed of the agricultural field throughout the rice harvest process is captured by a strategically placed camera, which forms the basis of this innovation. The Neural Stick is equipped with sophisticated AI and ML algorithms that process visual data in order to identify and tally the sacks that the Rice Reaper has filled. This automation technique is incredibly precise and effective. The addition of a GSM modem improves real-time capabilities by allowing communication over GSM networks and allowing the TCNVET_RSCMote to deliver alerts and updates in real time.
The Proximity Sensor is essential for accurately determining whether rice sacks are present or absent, which improves counting accuracy. The Buzzer can be set to sound alerts when it reaches a preset threshold, so operators are informed as soon as something noteworthy happens. One of the main components of this invention is cloud-based connectivity, which enables the system to deliver pertinent data to an internet-accessible mobile dashboard that is personalized. In order to give operators a centralized center from which to monitor the rice sack counting process in real time, this dashboard was created. In addition to enabling real-time updates, cloud connectivity guarantees that operators always have access to the most recent data and recommendations, which improves their ability to make decisions. Through an internet connection, operators can access the Tailored Mobile Dashboard remotely. From there, they can view the live feed, get real-time updates, and use the AI and ML-driven insights the system provides to make educated decisions.
BEST METHOD OF WORKING
The TCNVET_RSCMote, which has a BeagleBone Processor Board, Camera, GSM Modem, Neural Stick, Proximity Sensor, Buzzer, and Power Supply, is used to automate the precise counting and monitoring of rice sacks during harvesting. It also integrates real-time cloud connectivity for instant updates and provides operators with data-driven insights for improved decision-making.
The central processing unit of TCNVET_RSCMote, the BeagleBone Processor Board, enables effective coordination and communication to enable real-time AI and ML algorithms for precise rice sack counting during the harvesting process.
The TCNVET_RSCMote's integrated camera records live footage of the agricultural field, allowing vision-based technology to precisely analyze and count rice sacks during harvesting. This adds to the process's automation and accuracy.
The TCNVET_RSCMote's embedded GSM modem is utilized to enable real-time communication, allowing mote to communicate alarms and updates in real time over GSM networks. This ensures timely information and improves operator responsiveness during the rice harvesting process.
To improve the efficiency and precision of the system, TCNVET_RSCMote can process and analyze live video footage for precise rice sack counting during harvesting thanks to the Neural Stick interface, which is used to execute sophisticated AI and ML algorithms.
During harvesting, the Proximity Sensor interfaced in TCNVET_RSCMote is used to determine whether rice sacks are present or absent. This enhances the accuracy of the counting procedure and provides extra information for better monitoring and decision-making in agricultural settings.
ADVANTAGES OF THE INVENTION
1. The TCNVET_RSCMote uses cutting-edge vision-based technology to precisely and automatically count rice sacks as they are harvested, thereby optimizing agricultural processes. It incorporates cloud connectivity in real-time, giving operators instant updates and data-driven insights to improve decision-making.
2. The Camera records video of the farm in real time, which helps the vision-based technology of the TCNVET_RSCMote precisely assess and count rice bags during harvesting. This makes a substantial contribution to the process's overall automation and accuracy.
3. By enabling immediate connectivity, the GSM Modem enables TCNVET_RSCMote to broadcast real-time warnings and updates over GSM networks. During the rice harvesting process, this guarantees timely information and enhances operators' reaction.
4. A key component of the innovation is the Neural Stick, which uses cutting-edge AI and ML algorithms to interpret and analyze live camera images so that TCNVET_RSCMote can precisely count rice sacks during harvesting. This improves the precision and efficiency of the system.
5. The TCNVET_RSCMote's Proximity Sensor detects whether rice sacks are present or absent during harvesting, greatly enhancing the counting process' accuracy. It offers more information to improve agricultural field monitoring and decision-making.
, Claims:1. A system of vision-based edge technology for rice sack counting and monitoring in agricultural fields using rice reaper comprises TCNVET_RSCMote (100), which has a BeagleBone Processor Board (107), Camera (103), GSM Modem (101), Neural Stick (102), Proximity Sensor (106), Buzzer (105), and Power Supply (104), is used to automate the precise counting and monitoring of rice sacks during harvesting, it also integrates real-time cloud connectivity for instant updates and provides operators with data-driven insights for improved decision-making.
2. The system as claimed in claim 1, wherein the central processing unit of TCNVET_RSCMote, the BeagleBone Processor Board, enables effective coordination and communication to enable real-time AI and ML algorithms for precise rice sack counting during the harvesting process.
3. The system as claimed in claim 1, wherein the TCNVET_RSCMote's integrated camera records live footage of the agricultural field, allowing vision-based technology to precisely analyze and count rice sacks during harvesting, this adds to the process's automation and accuracy.
4. The system as claimed in claim 1, wherein the TCNVET_RSCMote's embedded GSM modem is utilized to enable real-time communication, allowing mote to communicate alarms and updates in real time over GSM networks, this ensures timely information and improves operator responsiveness during the rice harvesting process.
5. The system as claimed in claim 1, wherein to improve the efficiency and precision of the system, TCNVET_RSCMote can process and analyze live video footage for precise rice sack counting during harvesting thanks to the Neural Stick interface, which is used to execute sophisticated AI and ML algorithms.
6. The system as claimed in claim 1, wherein during harvesting, the Proximity Sensor interfaced in TCNVET_RSCMote is used to determine whether rice sacks are present or absent, this enhances the accuracy of the counting procedure and provides extra information for better monitoring and decision-making in agricultural settings.

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