Supervised and Unsupervised Data Engineering for Multimedia Data

5Unsupervised/Supervised Algorithms for Multimedia Data in Smart Agriculture

Reena Thakur^1*, Parul Bhanarkar² and Uma Patel Thakur¹

¹Jhulelal Institute of Technology, Nagpur, Maharashtra, India

²Symbiosis Skills and Professional University Pune Maharashtra, India

Abstract

Smart agriculture, a result of agriculture’s digital transformation, has seen the development of unsupervised and supervised algorithms for managing different parts of farm operations in order to get value from a flood of data from a variety of sources. In the agriculture industry, farmers and agribusinesses face many decisions every day, each of which is complicated by a wide range of interrelated issues. Accurately estimating yields for all the crops in a plan is crucial. The only way to effectively and practically solve this issue is to employ techniques of data mining. Artificial intelligence new branch, Machine learning, offers massive possibilities to overcome numerous difficulties in the expansion of knowledge-based agricultural schemes. Through a comprehensive review of the most up-to-date scholarly literature based on keyword combinations of “crop management” and “machine learning”, “soil management”, “water management”, and “livestock management”, this chapter aims to shed light on unsupervised and supervised algorithms in agriculture. It was also noted that crop management was the primary focus. In addition, studies on both maize and wheat, as well as cattle and sheep, were the most common. In ...