A survey on smart farming data, applications and techniques

Abstract

The Internet of Things (IoT) and the relevant technologies have had a significant impact on smart farming as a major sub-domain within the field of agriculture. Modern technology supports data collection from IoT devices through several farming processes. The extensive amount of collected smart farming data can be utilized for daily decision making and analysis such as yield prediction, growth analysis, quality maintenance, animal and aquaculture, as well as farm management. This survey focuses on three major aspects of contemporary smart farming. First, it highlights various types of big data generated through smart farming and makes a broad categorization of such data. Second, this paper discusses a comprehensive set of typical applications of big data in smart farming. Third, it identifies and introduces the principal big data and machine learning techniques that are utilized in smart farming data analysis. In doing so, this survey also identifies some of the major, current challenges in smart farming big data analysis.This paper provides a discussion on potential pathways toward more effective smart farming through relevant analytics-guided decision making.