AI based Plant Growth Monitoring System using Computer Vision

This research work aims to develop an AI-based plant growth monitoring system using computer vision. By leveraging computer vision algorithms and artificial intelligence techniques, the system will enable real-time and automated assessment of plant growth and health. Traditional methods for plant growth monitoring are time-consuming and labor-intensive. The proposed system will address these limitations by analyzing images of plants using image processing algorithms and extracting relevant features such as leaf area, plant height and width. Machine learning algorithms will be employed to train models capable of recognizing patterns and predicting plant growth based on the extracted features. The system will be designed to accommodate different plant types and environmental conditions. By providing accurate and timely insights into plant health and growth, this AI-based plant growth monitoring system will benefit farmers, researchers, and plant enthusiasts, enabling informed decision-making for plant care and optimizing growth conditions. This research work aims to revolutionize plant growth monitoring by offering a cost-effective, scalable, and efficient solution with wide applications in agriculture, horticulture and environmental research.