VISION-BASED COUNTER DEVICE FOR COUNTING PLUCKED APPLES VIA APPLE HARVESTER MACHINE IN APPLE ORCHARDS

Abstract

A vision-based counter device for counting plucked apples via apple harvester machine in apple orchards comprises VCBTD_AHMNode (100) is outfitted with a Raspberry Pi Processor (100I), Camera Module (100C), GPRS Modem (100A), Micro SD Card Module (100G), RTC Module, HMI Display (100H), Buzzer (100E), Indicator (100D), and Power Supply (100F), this allows for accurate and real-time counting of plucked apples as well as remote monitoring via IoT connectivity, greatly increasing productivity and efficiency in apple orchard operations accurate recognition and counting of plucked apples in the orchard are made possible by the Raspberry Pi Processor, which is employed as a processing unit in this innovation, it does this by using advanced vision algorithms to process live video data acquired by the camera module in real-time.

Specification

Description:FIELD OF THE INVENTION
This invention relates to vision-based counter device for counting plucked apples via apple harvester machine in apple orchards.
BACKGROUND OF THE INVENTION
This creative solution uses IoT connectivity and superior vision technology to provide a simplified method of counting apples that have been taken from orchards. The technology counts apples properly as the harvester gathers them because it records live video footage of apples being gathered and processes it instantly.
This idea aims to solve the inefficiencies and errors that come from manually counting apples that have been harvested in apple orchards during the harvesting process. Conventional techniques mostly rely on manual labor, which takes time and is prone to mistakes.
US20210133950A1: A machine vision based automatic needle cannula inspection system includes an inspection and control unit, image capture devices, light sources, a unit that makes the needle cannula and the image capture device(s) rotate relative to each other, and a rejected part removal unit. By means of rotating the needle cannula and image capture devices relatively, a plurality of images captured along the circumferential direction of the needle cannula are directly saved to a computer, the images are then screened, processed and analyzed to fulfill the automatic inspection of multiple quality and technical parameters of the needle cannula without the need to position the bevel area of cannula tip to a specific direction. Inspection parameters and accuracy can be set at any time, the system can automatically record classification and statistics of passed and rejected needle cannulae for query, and the rejected cannulae are removed automatically at next position. All the functions are completed at one work station, and needle cannula tips on both sides can be inspected simultaneously, if needed. Thereby the inspection efficiency and reliability are greatly improved, resulting in extremely extensive application prospects and huge economic values.
RESEARCH GAP: A Vision based addon technological device to count the plucked fruits for Apple Harvester Machine is the novelty of the system.
CN104483321B: The invention discloses a kind of injection needle automatic checkout system and detection method based on machine vision, including detection and control section, image capturing device, light source, the part and goods rejection part for injection needle is rotated against with image capturing device, the method rotated against using injection needle and image capturing device, several images, which are shot within one week, along injection needle circumferencial direction is directly stored in computer, pass through the screening to these images, handle and analyze to complete the automatic detection to the multiple quality of needle tubing and technical parameter, positioned without the opening direction to needle point.Detection parameter and precision can be set at any time, and system can record classification and the statistics of certified products and waste product automatically in case inquiry, waste product can be by automatic rejection.Institute is functional to complete in station, and the needle tubing that can have needle point to two ends carries out detection simultaneously, drastically increases the detection efficiency and reliability of needle tubing, with being extremely widely applied prospect and huge economic value.
RESEARCH GAP: A Vision based addon technological device to count the plucked fruits for Apple Harvester Machine 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 creative solution combines the power of vision technology, IoT connectivity, and user-friendly interfaces to enhance productivity and optimize the harvesting process. It provides a thorough and effective approach to count plucked apples in apple orchards. The device is first deployed onto the apple harvester machine and positioned so that it can clearly view the apples that have been harvested. The camera module records live video of the harvested apples as they go through the harvester as soon as the device is turned on. The Raspberry Pi Processor then processes this video input. It has training data sets specifically made to identify and count apples in a variety of settings, including varied lighting and orientations.
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 creative solution combines the power of vision technology, IoT connectivity, and user-friendly interfaces to enhance productivity and optimize the harvesting process. It provides a thorough and effective approach to count plucked apples in apple orchards. The device is first deployed onto the apple harvester machine and positioned so that it can clearly view the apples that have been harvested. The camera module records live video of the harvested apples as they go through the harvester as soon as the device is turned on. The Raspberry Pi Processor then processes this video input. It has training data sets specifically made to identify and count apples in a variety of settings, including varied lighting and orientations.
The Raspberry Pi Processor recognizes and counts the apples that have been plucked as the harvester gathers them by using cutting-edge vision technology to evaluate each frame of the video feed in real-time. Following that, the operator receives instant feedback regarding the quantity of apples gathered via the HMI (Human-Machine Interface) Display. The count data is simultaneously transmitted by the device to a customized user interface located on a local web dashboard through the use of IoT-based cloud technologies. Through the internet, operators can access this dashboard, log into their accounts, and remotely track the harvest process in real time. Operators can make well-informed decisions on the harvesting process by utilizing the count data, which is displayed in an easily navigable format, taking into account the current yield rates.
The gadget also has an RTC (Real-Time Clock) Module for precise timekeeping, a Micro SD Card Module for data storage, a GPRS Modem for wireless connection, and indicators like a buzzer for alerts and status updates. Together, these elements guarantee the VCBTD_AHMNode's dependable performance during the harvesting procedure.
BEST METHOD OF WORKING
Utilized as a vision-based device integrated onto apple harvester machines, the VCBTD_AHMNode is outfitted with a Raspberry Pi Processor, Camera Module, GPRS Modem, Micro SD Card Module, RTC Module, HMI Display, Buzzer, Indicator, and Power Supply. This allows for accurate and real-time counting of plucked apples as well as remote monitoring via IoT connectivity, greatly increasing productivity and efficiency in apple orchard operations.
Accurate recognition and counting of plucked apples in the orchard are made possible by the Raspberry Pi Processor, which is employed as a processing unit in this innovation. It does this by using advanced vision algorithms to process live video data acquired by the camera module in real-time.
Another component of the VCBTD_AHMNode is the Camera Module, which records live video of apples being harvested as they go through the harvester. This visual data helps the Raspberry Pi Processor analyze and precisely count the apples as they are being plucked in real time.
The built-in GPRS modem in the VCBTD_AHMNode enables wireless connection. By sending count data to a customized user interface housed on a local web dashboard, the VCBTD_AHMNode may transfer data remotely and provide operators with real-time online harvest process monitoring.
The HMI Display, which is interfaced with the VCBTD_AHMNode, is utilized as a Visual Output device to show the number of apples that have been plucked in real time. This improves decision-making on the spot and makes it easier to manage the orchard's harvest process effectively.
ADVANTAGES OF THE INVENTION
1. The VCBTD_AHMNode is a comprehensive, vision-based device that is integrated into apple harvester machines. It allows for accurate and real-time counting of plucked apples and allows for remote monitoring via Internet of Things connectivity. As a result, it greatly increases productivity and efficiency in apple orchard operations.
2. The Camera Module records live video of apples being harvested as they go through the harvester, giving the Raspberry Pi Processor visual data to evaluate and precisely count the apples as they are gathered in real time.
3. The VCBTD_AHMNode may send count data to a customized user interface located on a local web dashboard thanks to the GPRS Modem, which enables wireless connectivity. This allows operators to remotely monitor harvest progress in real-time over the internet.
4. By showing the number of apples that have been plucked in real time, the HMI Display gives operators instant feedback, improving decision-making on the spot and enabling effective administration of the orchard's harvest procedure.
, Claims:1. A vision-based counter device for counting plucked apples via apple harvester machine in apple orchards comprises VCBTD_AHMNode (100) is outfitted with a Raspberry Pi Processor (100I), Camera Module (100C), GPRS Modem (100A), Micro SD Card Module (100G), RTC Module, HMI Display (100H), Buzzer (100E), Indicator (100D), and Power Supply (100F), this allows for accurate and real-time counting of plucked apples as well as remote monitoring via IoT connectivity, greatly increasing productivity and efficiency in apple orchard operations.
2. The device as claimed in claim 1, wherein accurate recognition and counting of plucked apples in the orchard are made possible by the Raspberry Pi Processor, which is employed as a processing unit in this innovation, it does this by using advanced vision algorithms to process live video data acquired by the camera module in real-time.
3. The device as claimed in claim 1, wherein another component of the VCBTD_AHMNode is the Camera Module, which records live video of apples being harvested as they go through the harvester, this visual data helps the Raspberry Pi Processor analyze and precisely count the apples as they are being plucked in real time.
4. The device as claimed in claim 1, wherein the built-in GPRS modem in the VCBTD_AHMNode enables wireless connection, by sending count data to a customized user interface housed on a local web dashboard, the VCBTD_AHMNode may transfer data remotely and provide operators with real-time online harvest process monitoring.
5. The device as claimed in claim 1, wherein the HMI Display, which is interfaced with the VCBTD_AHMNode, is utilized as a Visual Output device to show the number of apples that have been plucked in real time, this improves decision-making on the spot and makes it easier to manage the orchard's harvest process effectively.

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