Plant-Classification-and-Care-Recommandations

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AUTOMATIC PLANT DETECTION AND CARE RECOMMENDATIONS USING OPENCV AND MACHINE LEARNING TECHNIQUES

Due to its many advantages, including bettering air quality, lowering stress levels, and providing fresh produce, indoor gardening is growing in popularity. Since indoor environments lack natural elements like sunlight and rainfall, which are crucial for plant growth, maintaining indoor plants can be difficult.

As a result, several technologies have been created to assist indoor gardeners in providing their plants with the best possible growing circumstances.

One such technology is computer vision and artificial intelligence (AI), which may be used to, among other things, detect plant height and age, leaf disease, and precise watering instructions.

● OBJECTIVE:-

1. The purpose of this research article is to investigate the application of artificial intelligence (AI) and computer vision to indoor gardening, with an emphasis on the identification of plant height and age, leaf disease, and adequate watering instructions.

2. The research also discusses further AI methods that can be used to enhance indoor illumination, watering schedules, soil quality, and pest identification.

3. The ultimate objective is to offer indoor gardeners resource-saving, effective, and sustainable options for plant development.

● KEY POINTS:-

1. Indoor gardening is growing more and more popular, but without natural components like sunlight and rain, sustaining plants can be difficult.

2. AI and computer vision can be used to identify plant height and age, identify leaf disease, and offer instructions on how much water to use.

3. Machine learning models can be used to estimate plant age based on height and other features, while computer vision algorithms can be used to determine plant height from photographs of the plant.

4. Indoor gardeners can quickly take action to stop the spread of illness by using computer vision algorithms that have been trained on photos of both healthy and diseased plants.

5. AI algorithms can be used to calculate the quantity of water a plant needs based on its leaf density.

● PROPOSED ALGORITHM:-

STEP 1:- Plant Height and Age Detection: Capture images of the plant from different angles using cameras or handheld devices

Preprocess the images to enhance the quality and eliminate any background noise

Use computer vision algorithms, such as object detection or segmentation, to detect the plant and determine its height based on the size of the plant in the image

Collect data from plants of known age and height and use it to train a machine learning model, such as regression, to estimate the age of new plants based on their height and other characteristics.

STEP 2:- Leaf Disease Detection: Collect images of healthy and diseased plants

Preprocess the images to standardize the quality and eliminate any background noise

Train computer vision algorithms, such as convolutional neural networks (CNNs), on the images to detect signs of leaf disease

Analyze new images of plant leaves using the trained algorithms to identify any signs of disease

Take timely action to prevent the spread of disease and improve plant health and quality.

STEP 3:- Leaf Density and Proper Watering Guidance: Collect data from plants of different leaf densities and corresponding watering schedules

Train AI algorithms, such as decision trees or random forests, on the data to estimate the amount of water required by a new plant based on its leaf density

Use the algorithms to provide proper watering guidance, reducing water use while maintaining plant health and quality.

● WORKING MODEL:-

● CONCLUSION :-

With innovative approaches to age-old problems, computer vision and AI have the power to completely transform indoor gardening.Indoor gardeners may optimize plant development, use fewer resources, and increase the health and quality of their plants by detecting plant height and age, leaf disease, and leaf density. AI can also be used to monitor soil conditions, identify pests, and optimize lighting and watering schedules, making indoor gardening more effective and sustainable. We may anticipate even more cutting-edge AI uses in indoor gardening as these technologies develop, enhancing plant sustainability and health for everyone.

By:- Mehul Ligade, Pranav Khandagale, Pratik Gidde, Akansha Karande