Plantosphere: Next Generation Adaptive and Smart Agriculture System

Abstract

Around 75% of the population in India is engaged in agriculture and farming. The sustainability of every economy is based on agriculture. It has a major influence on financial growth and fundamental transformation in the long run. Artificial intelligence will usher in a revolution in agricultural operations in the future. This revolution has protected crops from being negatively affected by a variety of factors such as climate change, soil porosity, and water availability. Crop monitoring, soil management, and insect identification, to name a few examples, are all conceivable uses of artificial intelligence in agriculture. The primary purpose of artificial intelligence is to close the knowledge gap that exists between inventors and farmers. Detecting disease and monitoring plant health are two of the most difficult challenges in sustainable farming. As a result, image processing technology must be used to detect plant sickness at an early stage. Photographic capture, preprocessing, segmentation, feature extraction, and sickness categorization are all part of the procedure. In reality, computer image processing was used long before human eyes were able to detect the signs and symptoms of the disease. Taking into account the climatic conditions in various parts of the world. Climate change directly affects crop output. Several soil and atmospheric characteristics are detected to anticipate the optimal crop. Sedimentation is measured by soil parameters such as pH and moisture. Today, a platform that allows farmers to advertise their products is in high demand. This paper proposes a system where farmers sell directly to clients, bypassing wholesalers and traders. A predictive analytics solution is required to maximize the farmer’s profit.