Smart Crops Monitoring Using New Computer Vision Iot System

Abstract

Modern Agriculture is undergoing a significant transformation through Artificial Intelligence (AI) in Crop Management by aligning with sustainable goals and enhances resilience. Forecasting of crop outbreaks, Pest infestations and disease outbreaks, predicting extreme weather events empowers to farmers make real time data driven decisions that they will receive timely alert and recommendations improving productivity and less environmental impacts on crop with the help of predictive analysis of AI-driven tools for more accurate forecasting of crops. IOT based technologies like Smart Crop selection (SCS) is based on real time monitoring, predictive analytics, reduce input costs, site specific environmental and soil data, weather data.

Hydroponic methods of plants growing used water based, nutrient rich solutions and controls environment agriculture like optimize light exposure, protects crop from pests, (aquaculture, Nutri culture, drip system) crops with high quality. Depending upon crop cycle and scale hydroponic system used greenhouses which provided controlled environment for growing system of crops. Development of resilient crops related to abiotic stress, biotic stress and unpredictable climate change identified by the AI-driven tools, which is useful for increasing farming systems, enhance predictive models for increase food demands and integration with enhanced IOT. The goal to optimize inputs (water, pesticides, fertilizer) and maximum sustainability an advanced method of farming Precision agriculture techniques are used. This method uses technology to monitoring, measurement, analyze complex datasets for more accurate recommendations for variability in crops and fields.