The agriculture sector is undergoing a transformation driven by new technologies, which seems very promising as it will enable this primary sector to move to the next level of farm productivity and profitability. Precision Agriculture, which consist of applying inputs (what is needed) when and where is needed, has become the third wave of the modem agriculture revolution (the first was mechanization and the second the green revolution with its genetic modification), and nowadays, it is being enhanced with an increase of farm knowledge systems due to the availability of larger amounts of data. The Ministry of Agriculture and Farmers Welfare (formerly Ministry of Agriculture) already reported in October 2019 that Precision Agriculture technologies increased net returns and operating profits. Also, when considering the environment, new technologies are increasingly being applied in the farms to maintain the sustainability of farm production. However, the adoption of these technologies involves uncertainty and trade-offs. According to a market analysis, the factors that would facilitate the adoption of sustainable farming technologies include better education and training of farmers, sharing of information, easy availability of financial resources, and increasing consumer demand for organic food. When applying these new technologies, the challenge for retrieving data from crops is to come out with something coherent and valuable, because data themselves are not useful, just numbers or images. Farms that decide to be technology-driven in some way, show valuable advantages, such us saving money and work, having an increased production or a reduction of costs with minimal effort, and producing quality food with more environmentally friendly practices. However, taking these advantages to the farm will depend, not only on the willingness of producers. The automation in agriculture is the main concern and the emerging subject across the world. The population is increasing tremendously and with this increase the demand of food and employment is also increasing. The traditional methods which were used by the farmers, were not sufficient enough to fulfill these requirements. Thus, new automated methods were introduced. These new methods satisfied the food requirements and also provided employment opportunities to billions of people. Machine learning in agriculture has brought an agriculture revolution. This technology has protected the crop yield from various factors like the climate changes, population growth, Diseases, which is best fertilizer for crop employment issues and the food security problems.