Sustainable Algorithms using Artificial Intelligence and Various Stages for Precision Agricultural Cultivation

India, the largest exporter of farm products, faces low agricultural productivity, resulting in reduced income for farmers. To boost revenue, performance improvement is crucial. Irrigation plays a vital role in farming, necessitating careful management of soil moisture levels. However, traditional irrigation methods often lead to water wastage. Efficient utilization of land and resources is essential in addressing this issue. Pest attacks pose a significant threat to crop yield and quality, making pest identification critical. Farmers and agronomists now utilize sensors and IoT technology to remotely monitor crops and manage them in controlled environments. However, crop productivity is still affected by weather conditions and disease variations. Precise detection of plant deficiencies and accurate fertilizer deployment is crucial for efficient farming. Modern computer vision techniques can be leveraged for positive financial and environmental outcomes in these tasks. Good crop selection significantly impacts yield, especially in developing countries. Additionally, growing vegetables in greenhouses or hydroponics offers a promising solution to discontinuous and costly supply chains. This abstract highlights the importance of addressing productivity challenges and implementing innovative farming methods to enhance agricultural outcomes.