Description:Title of The Invention
PLANT HEALTH INDICATOR DEVICE USING EDGE DEVICE AND CLOUD SERVER
Field of the Invention
This invention relates to plant health indicator device using edge device and cloud server
Background of the Invention
US10993430B2: Reliable machine recognition of plant identity (crop vs. weed) is a major impediment to the commercial development of automated plant care systems such as automatic weed control machines that can reliably control intra - row weeds on a farm. Existing crop monitoring systems typically utilize machine vision technology to detect plant location and accurately direct herbicidal sprays, to thin crops, like lettuce, to desired stands. However, the current state - of - the - art in this technology cannot reliably distinguish crop from weed plants, but depends upon recognition of row patterns to detect the crop row, and rudimentary object detection for selection of unwanted crop plants for thinning. Research on these systems shows that while such systems may work well in weed - free fields, their performance is limited in weedy fields, which obscure the row pattern.
US7607257B2: An automatic plant watering apparatus having a cavity for receiving a standard houseplant pot, a reservoir for holding water, a pump for removing water from the reservoir, a host for delivering water from the pump to a plant positioned in the cavity. The pump is operated by a microcontroller that is programmed to measure a first time period during which the pump is not operated, and a second time period during which the pump is operated. According, the apparatus can be programmed to automatically water a house plant at predetermined intervals, as well as deliver a predetermined amount of water.
None of the prior art indicate above either alone or in combination with one another disclose what the present invention has disclosed. Present invention is high variability in plant morphology, which makes it difficult to develop robust algorithms that can accurately differentiate between crops and weed plants. Moreover, the performance of these systems can be significantly impacted by environmental factors such as lighting conditions, soil type, and the presence of other vegetation.
Another limitation of existing crop monitoring systems is their dependence on row patterns for crop detection. In weedy fields, where the weeds grow between the crop rows or in the same row as the crops, the row pattern may not be distinguishable, leading to inaccurate plant identification.
Additionally, some weed species closely resemble crop plants, making it challenging to differentiate between them based on visual characteristics alone. In such cases, other modalities such as spectral or chemical analyses may need to be incorporated to improve recognition accuracy.
Despite these challenges, researchers are exploring various approaches to improve the reliability of machine recognition of plant identity. These include the use of advanced machine learning algorithms, multi-spectral imaging, and 3D imaging technologies that can provide additional information on plant structure and texture. Additionally, the development of hybrid systems that combine machine vision with other sensing modalities may offer a more comprehensive solution to the problem of crop-weed differentiation in automated plant care systems.
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.
There are a variety of factors that determine the health and growth of plants, including but not limited to water, sunlight, temperature, nutrients, and soil quality. However, keeping track of all of these variables can be difficult, especially for those who are new to gardening or have limited experience with plant care. One common issue that arises does not know how much water a plant needs. Overwatering can be just as harmful as under watering, and the optimal amount of water can vary depending on factors such as the type of plant, the size of the pot or garden bed, and the climate. Similarly, plants have varying requirements for sunlight, with some preferring full sun exposure while others thrive in partial shade. In addition to water and sunlight, it is important to consider other basic needs such as the type and amount of nutrients required for healthy growth, as well as the pH and texture of the soil. Neglecting these factors can lead to stunted growth, disease, or even death of the plant. Given these complexities, it can be overwhelming to try to remember all of the necessary details for each individual plant in your care. One solution is to research the needs of each plant before adding it to your garden, and keeping track of its specific requirements in a gardening journal or app. This can help you develop a routine that ensures each plant is getting the right amount of water, sunlight, and nutrients on a consistent basis. Another helpful strategy is to pay close attention to your plants and observe any changes in their appearance or behavior. Wilting leaves or yellowing foliage can be signs of over or under watering, while plants that are not receiving enough sunlight may become leggy or spindly. By being attentive and responsive to the needs of your plants, you can provide them with the best possible environment for healthy growth and a fruitful harvest. PHI consists of a set of small, low-power sensor nodes distributed over a large area. Each node is equipped with sensors that can measure various physical and environmental parameters such as temperature, humidity, light, and pressure.
These sensor nodes are connected to a cloud server that stores data and acts as a mediator between the plant and the user. The PHI device also contains a computing unit that is connected to sensors (temperature, moisture, PT, NPR) and AI (Artificial intelligence). The sensors detect the working or growth of the plant, and this information is sent by sensors to the computing unit. After receiving data from the sensors, the AI analyzes the data and sends it to your mobile application. The AI can provide recommendations on what your plant needs to thrive based on the data analysis.
Overall, the PHI (Plant Health Indicator) helps collecting data from sensors distributed over a large area, processing the data using AI, and providing recommendations to the user via a mobile application. By using this system, users can monitor their plants and take necessary actions to ensure their plants grow and thrive.
An edge-based sensor node system is a type of networked sensing system that consists of a set of small, low-power sensor nodes distributed over a large area. Each node is equipped with sensors that can measure various physical and environmental parameters such as temperature, humidity, light, and pressure.
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: There are a variety of factors that determine the health and growth of plants, including but not limited to water, sunlight, temperature, nutrients, and soil quality. However, keeping track of all of these variables can be difficult, especially for those who are new to gardening or have limited experience with plant care. One common issue that arises does not know how much water a plant needs. Overwatering can be just as harmful as under watering, and the optimal amount of water can vary depending on factors such as the type of plant, the size of the pot or garden bed, and the climate. Similarly, plants have varying requirements for sunlight, with some preferring full sun exposure while others thrive in partial shade. In addition to water and sunlight, it is important to consider other basic needs such as the type and amount of nutrients required for healthy growth, as well as the pH and texture of the soil. Neglecting these factors can lead to stunted growth, disease, or even death of the plant. Given these complexities, it can be overwhelming to try to remember all of the necessary details for each individual plant in your care. One solution is to research the needs of each plant before adding it to your garden, and keeping track of its specific requirements in a gardening journal or app. This can help you develop a routine that ensures each plant is getting the right amount of water, sunlight, and nutrients on a consistent basis. Another helpful strategy is to pay close attention to your plants and observe any changes in their appearance or behavior. Wilting leaves or yellowing foliage can be signs of over or under watering, while plants that are not receiving enough sunlight may become leggy or spindly. By being attentive and responsive to the needs of your plants, you can provide them with the best possible environment for healthy growth and a fruitful harvest. PHI consists of a set of small, low-power sensor nodes distributed over a large area. Each node is equipped with sensors that can measure various physical and environmental parameters such as temperature, humidity, light, and pressure.
These sensor nodes are connected to a cloud server that stores data and acts as a mediator between the plant and the user. The PHI device also contains a computing unit that is connected to sensors (temperature, moisture, PT, NPR) and AI (Artificial intelligence). The sensors detect the working or growth of the plant, and this information is sent by sensors to the computing unit. After receiving data from the sensors, the AI analyzes the data and sends it to your mobile application. The AI can provide recommendations on what your plant needs to thrive based on the data analysis.
Overall, the PHI (Plant Health Indicator) helps collecting data from sensors distributed over a large area, processing the data using AI, and providing recommendations to the user via a mobile application. By using this system, users can monitor their plants and take necessary actions to ensure their plants grow and thrive.
An edge-based sensor node system is a type of networked sensing system that consists of a set of small, low-power sensor nodes distributed over a large area. Each node is equipped with sensors that can measure various physical and environmental parameters such as temperature, humidity, light, and pressure.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.
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.
It should be noted that the description merely illustrates the principles of the present subject matter. It will thus be appreciated that those skilled in the art will be able to devise various arrangements that, although not explicitly described herein, embody the principles of the present subject matter and are included within its scope.
Overwatering can be just as harmful as under watering, and the optimal amount of water can vary depending on factors such as the type of plant, the size of the pot or garden bed, and the climate. Similarly, plants have varying requirements for sunlight, with some preferring full sun exposure while others thrive in partial shade. In addition to water and sunlight, it is important to consider other basic needs such as the type and amount of nutrients required for healthy growth, as well as the pH and texture of the soil. Neglecting these factors can lead to stunted growth, disease, or even death of the plant. Given these complexities, it can be overwhelming to try to remember all of the necessary details for each individual plant in your care. One solution is to research the needs of each plant before adding it to your garden, and keeping track of its specific requirements in a gardening journal or app. This can help you develop a routine that ensures each plant is getting the right amount of water, sunlight, and nutrients on a consistent basis. Another helpful strategy is to pay close attention to your plants and observe any changes in their appearance or behavior. Wilting leaves or yellowing foliage can be signs of over or under watering, while plants that are not receiving enough sunlight may become leggy or spindly. By being attentive and responsive to the needs of your plants, you can provide them with the best possible environment for healthy growth and a fruitful harvest. PHI consists of a set of small, low-power sensor nodes distributed over a large area. Each node is equipped with sensors that can measure various physical and environmental parameters such as temperature, humidity, light, and pressure.
The PHI device also contains a computing unit that is connected to sensors (temperature, moisture, PT, NPR) and AI (Artificial intelligence). The sensors detect the working or growth of the plant, and this information is sent by sensors to the computing unit. After receiving data from the sensors, the AI analyzes the data and sends it to your mobile application. The AI can provide recommendations on what your plant needs to thrive based on the data analysis.
Overall, the PHI (Plant Health Indicator) helps collecting data from sensors distributed over a large area, processing the data using AI, and providing recommendations to the user via a mobile application. By using this system, users can monitor their plants and take necessary actions to ensure their plants grow and thrive.
An edge-based sensor node system is a type of networked sensing system that consists of a set of small, low-power sensor nodes distributed over a large area. Each node is equipped with sensors that can measure various physical and environmental parameters such as temperature, humidity, light, and pressure.
ADVANTAGES OF THE INVENTION:
• Plant health indicators are tools that help growers and researchers assess the overall health and condition of plants.
• Plant health indicators can provide early warning signs of plant stress, nutrient deficiencies, or disease outbreaks.
• By monitoring plant health indicators, growers can optimize plant growth and production by adjusting nutrient applications, irrigation schedules, and other management practices.
, Claims:We Claim:
1. Plant health indicator device using edge device and cloud server system is comprises with Computing Unit (10), Temperature Sensor (11), Moisture Sensor (12), pH Sensor (13),NPK Sensor (14), Battery Power Supply (15),AI Model (16), Relay Unit (17), WiFi Module (18), Display (19), and Water pipe valve (20).
2. The system as claimed in claim 1, wherein sensor nodes are connected to a cloud server that stores data and acts as a mediator between the plant and the user.
3. The system as claimed in claim 1, wherein the PHI device also contains a computing unit is connected to sensors (temperature, moisture, PT, NPR) and AI (Artificial intelligence).
4. The system as claimed in claim 1, wherein sensors detect the working or growth of the plant, and this information is sent by sensors to the computing unit.
5. The system as claimed in claim 1, wherein after receiving data from the sensors, the AI analyzes the data and sends it to your mobile application; the AI provides recommendations on what your plant needs to thrive based on the data analysis.
6. The system as claimed in claim 1, whereinthe PHI (Plant Health Indicator) helps collecting data from sensors distributed over a large area, processing the data using AI, and providing recommendations to the user via a mobile application.
7. The system as claimed in claim 1, wherein by using this system, users can monitor their plants and take necessary actions to ensure their plants grow and thrive.
8. The system as claimed in claim 1, wherein an edge-based sensor node system is a type of networked sensing system that consists of a set of small, low-power sensor nodes distributed over a large area.
9. The system as claimed in claim 1, wherein Each node is equipped with sensors that can measure various physical and environmental parameters such as temperature, humidity, light, and pressure.