Smart Agritech

7Data Analytics in Agriculture: Predictive Models and Real-Time Decision-Making

Raman Kumar¹, Harpreet Kaur Channi²* and Harish Kumar Banga³

¹Department of Mechanical and Production Engineering, Guru Nanak Dev Engineering College, Ludhiana, Punjab, India

²Department of Electrical Engineering, Chandigarh University, Gharuan, Mohali, India,

³Department of Fashion & Lifestyle Accessories Design, National Institute of Fashion Technology, Kangra, Himachal Pradesh, India

Abstract

The agricultural sector increasingly uses data analytics to help with decision-making. Predictive models and real-time decision-making are essential components of data analytics effectively utilized in agriculture. An overview of these ideas, their significance in agriculture, and their implementations in the sector are given in this chapter. The chapter begins by discussing the difficulties in gathering and organizing agricultural data and methods for doing so successfully. The discussion of predictive models then goes in-depth, covering the many kinds employed in agriculture, their uses, and instances of successful predictive modelling in agriculture. The necessity of real-time decision-making in agriculture, the methods and techniques employed, and successful instances are all covered in this section. In addition, the chapter covers the advantages, difficulties, and approaches for incorporating predictive models and real-time decision-making in agriculture. Lastly, the possible uses and ramifications ...