Predictive analysis in smart agriculture

Title

Predictive analysis in smart agriculture

Creator

Balaji S.; Ashok J.; Selvaraju P.; Gangwar V.P.

Description

Analyzing large databases for hidden connections, correlations and insights is known as big data analytics. Although many countries still use outdated farming methods, technological advancements have allowed for specific improvements (especially in developing countries). Big data analytics has the potential to expand the agricultural sector in this regard significantly. The farmers rely heavily on old methods for deciding what to plant and how to cultivate it. Walking through fields, selecting soil samples for moisture analysis, and visually inspecting plant leaves are typical examples of these time-honored practices. Understanding the significance of technology for acquiring crop information in considerable amounts and turning that data into usable knowledge is crucial for agriculturists (mainly farmers). Integration of big data could help agriculture make changes to its current practices. If used correctly, big data analytics can shed light on the most efficient crop cultivation methods. Extensive developments in three areas-crop prediction, precision farming and seed production-are reshaping the agricultural industry. There are four parts to this chapter. The first part of this paper provides an introduction to analytics on big data in agriculture. The second part will then focus on the various big data methods used in the agricultural sector. The third section provides two examples of how big data analysis methods were put to use in the field of agriculture. In the fourth section, the authors examine the several agricultural research avenues open to scholars and scientists. This chapter concludes with a brief overview. 2023 River Publishers. All rights reserved.

Source

Advanced Technologies for Smart Agriculture, pp. 105-127.

Date

2023-01-01

Publisher

River Publishers

Coverage

Balaji S., Department of Electrical and Electronics Engineering, SRM Valliammai Engineering College, India; Ashok J., School of Business and Management, CHRIST (Deemed to be University), India; Selvaraju P., Department of Mathematics, Rajalakshmi Institute of Technology, India; Gangwar V.P., Department of General Marketing, Mittal School of Business, Lovely Professional University, India

Rights

Restricted Access

Relation

ISBN: 978-877022883-1; 978-877022848-0

Format

Online

Language

English

Type

Book chapter

Identifier

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175668892&partnerID=40&md5=1e0f9587cc6c9a4a5997450fde263b3a