The demands of population are gradually increasing rapidly. Most manufacturing and processing industries face obstacles or problems to fulfil this daily increase in demand. Even if the demand can be managed, the transmission of diseases through these sectors is also a considerable concern. Many new technologies are being used to avoid unbearable consequences, which arise because of human-to-human contact or interaction. Higher firms adopt a ton of computer software and other modern technologies to get rid of such problems. Farming, one among the essential professions is also being impacted; however, human beings have come a long way since they started farming. This paper examines how one of the latest technologies, Artificial Intelligence, has helped improve farming, agriculture, and related tasks to increase yield and productivity. How Animal Farming, Detection of Diseases in Plants, Grading processes of Agricultural Foods, and quality check of vegetables and fruits, have advanced with the aid of Artificial Intelligence, is summed up in the subsequent sections.
The consistent advancement of innovation has implied information and data being created at a rate, not at all like ever previously, and it's just on the ascent. The world makes an extra 2.5 quintillion bytes of information every year. The demand for individuals talented in investigating, deciphering, and utilising this information is now high and is set to become exponential over the coming years. The total populace is relied upon to arrive at 9.7 billion by 2050 from the current population of 7.8 billion. The Food and Agriculture Organization (FAO) has predicted that the development of farming must be expanded by 70% to provide for the extended interest. Data-driven agriculture choices can be a potent technology to manage the needs of this much high population, as this technology gives higher efficiency, rehearses support-ability, and even assists with giving straightforwardness to purchasers and consumers needing to find out about their food as reported in the studies. The current and future interests will require more data researchers, data engineers, data specialists, and chief data Officers. This paper tries to examine the need, use, role, and issues faced by data science and data analytics to improve the quality as well as quantity of Agricultural produce thereby leading to an increase in production, a decrease in costs, and overall sustainability.
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