Smart Farming Using Machine Learning and Deep Learning: A Review

About 70% of the Indian population is dependent on agriculture, making it an agricultural nation. Economy of India highly depends on agriculture, the agricultural industry contributes one-third of the income in our country. The agriculture sector has a great impact on the nation's Gross Domestic Product (GDP). Until long, farmers have relied on conventional farming techniques. Crop productivity is reduced by these ineffective, time-consuming procedures. Digital farming boosts output by accurately determining the actions that must be conducted at the right time of year. Weather forecasting, classification of soil, crop suggestion, and determining how much fertilizers and insecticide to use are a few aspects of digital farming. Precise Farming gathers data, trains systems, and forecasts outcomes using cutting-edge technologies including IOT (Internet of Things), Data Mining, Data Analytics, and Machine Learning. Digital farming increases production by reducing manual labor. Farmers are struggling with numerous issues like Low rainfall, failed crops, crop diseases, etc. The proposed study aids in determining the soil's quality, recommends which crop to plant based on the climate, and makes fertilizers recommendations to raise the soil's fertility. The purpose of this activity is to assist a person in efficiently cultivating crops and achieving high yield.