WEED IDENTIFICATION AND MONITORING THROUGH INNOVATIVE IOT-BASED SENSOR DEVICE

Abstract

This invention introduces an IoT-based sensor device that detects and identifies weeds in real time using image and chlorophyll sensors. The portable device, which can be used as a smartphone-integrated system or standalone, provides farmers with immediate insights into weed presence and plant health. By automating weed detection, this device supports sustainable agriculture, reduces labor, and enhances productivity.

Specification

Description:FIELD OF THE INVENTION
This invention relates to agricultural technology, specifically an Internet of Things (IoT)-based sensor device designed to detect and identify weeds in real time. This device leverages advanced sensor integration and machine learning algorithms to enhance agricultural productivity by facilitating accurate, efficient weed management and plant health monitoring.
BACKGROUND OF THE INVENTION
Weeds present significant challenges in agriculture, as they compete with crops for essential resources like water, nutrients, and sunlight. The competition from weeds reduces crop yields, compromises plant health, and increases the overall cost of cultivation. Traditionally, farmers rely on manual methods or chemical herbicides for weed management. While herbicides are effective, they contribute to environmental pollution, pose health risks to farmers, and can lead to herbicide-resistant weed strains. Manual weeding is labor-intensive, time-consuming, and less effective, especially in large agricultural fields.
Advancements in precision agriculture have highlighted the potential of technology-based solutions for weed management. Image processing, chlorophyll sensing, and machine learning are being explored as promising methods to automate weed detection and identification. However, existing solutions often lack portability, real-time data processing, and flexibility, limiting their application in diverse agricultural settings. Furthermore, traditional sensor systems are not integrated into user-friendly platforms accessible to farmers on-site, thus constraining their practicality in field conditions.
This invention aims to address these limitations by introducing an IoT-enabled, portable sensor device that identifies weeds based on image and chlorophyll data, processes the information in real time, and provides actionable insights to farmers through a smartphone or portable device. The solution reduces dependency on herbicides, lowers labor costs, and aligns with sustainable agricultural practices, making it ideal for diverse agricultural applications.
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.
This invention is an IoT-based sensor system designed to detect and identify weeds in agricultural fields. The system includes image and chlorophyll sensors that capture data from plant surfaces, and machine learning algorithms that analyze this data to identify weeds accurately. The device is portable and can be integrated into a smartphone or used as a standalone tool, providing farmers with real-time information on weed presence and plant health. This approach promotes efficient, eco-friendly weed management, reduces labor costs, and enhances overall agricultural productivity.
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: ILLUSTRATES THE IOT-BASED SENSOR DEVICE AND ITS COMPONENTS, INCLUDING THE IMAGE SENSOR, CHLOROPHYLL SENSOR, AND MICROCONTROLLER.
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 invention comprises an IoT-based sensor device designed to automate weed identification and monitoring in agricultural fields. The device integrates an image sensor, a chlorophyll sensor, a microcontroller, and wireless connectivity for data transmission. The image sensor captures visual data from plants, including color, shape, and texture, while the chlorophyll sensor measures chlorophyll content, which is indicative of plant health. Together, these sensors provide a comprehensive dataset for distinguishing weeds from crops.
A microcontroller manages the sensor inputs and processes the captured data. The data is transmitted to a central server for real-time processing, where machine learning algorithms analyze the information. The image data is processed using shape and color analysis, identifying weeds based on their distinct morphological features. Chlorophyll levels are also assessed to determine plant health, allowing the system to differentiate between healthy plants and potential weed threats. This analysis is then conveyed back to the farmer's device, offering immediate insights.
The device can be used in two configurations: as a smartphone-integrated system or as a standalone portable unit. When used with a smartphone, the device connects via Bluetooth or Wi-Fi, enabling farmers to access real-time weed detection results directly on their phones. Alternatively, the standalone unit provides alerts and diagnostics through a built-in interface, making it versatile and adaptable to different field conditions. This flexibility allows farmers to use the device for regular monitoring, early weed detection, and crop health assessment, reducing reliance on chemical herbicides and promoting sustainable practices.
The system is designed for durability and ease of use, with a weather-resistant casing suitable for outdoor environments. The user interface offers intuitive icons and alerts, simplifying the identification process. Additionally, the data collected by the device can be stored for trend analysis, enabling farmers to monitor weed prevalence over time and adjust their management practices accordingly. By automating weed detection and plant health monitoring, the device enhances agricultural productivity, minimizes manual labor, and supports environmentally responsible farming.
, Claims:1. An IoT-based sensor device for weed identification and monitoring in agriculture, comprising an image sensor, a chlorophyll sensor, and a microcontroller.
2. The device as claimed in Claim 1, wherein the image sensor captures visual data from plants, including color, shape, and texture, to distinguish weeds from crops.
3. The device as claimed in Claim 1, wherein the chlorophyll sensor measures chlorophyll levels to assess plant health and differentiate healthy plants from potential weeds.
4. The device as claimed in Claim 1, wherein the microcontroller processes sensor inputs and transmits data to a central server for real-time analysis.
5. The device as claimed in Claim 1, wherein machine learning algorithms analyze image and chlorophyll data to identify weeds based on distinct morphological features.
6. The device as claimed in Claim 1, wherein it can connect to a smartphone via Bluetooth or Wi-Fi for real-time weed detection and monitoring results.
7. The device as claimed in Claim 1, wherein it operates as a standalone unit with a built-in user interface, providing alerts and diagnostics in the field.
8. A method for using the IoT-based sensor device as claimed in Claim 1 for real-time weed identification, involving data capture, transmission, and analysis to provide actionable insights.
9. The device as claimed in Claim 1, wherein it is designed with a weather-resistant casing for durability in outdoor agricultural environments.

10. The device as claimed in Claim 1, wherein it supports sustainable agricultural practices by reducing herbicide dependency and labor costs in weed management.

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