Data analytics platforms for agricultural systems: A systematic literature review

With the rapid developments in ICT, the current agriculture businesses have become increasingly data-driven and are supported by advanced data analytics techniques. In this context, several studies have investigated the adopted data analytics platforms in the agricultural sector. However, the main characteristics and overall findings on these platforms are scattered over the various studies, and to the best of our knowledge, there has been no attempt yet to systematically synthesize the features and obstacles of the adopted data analytics platforms. This article presents the results of an in-depth systematic literature review (SLR) that has explicitly focused on the domains of the platforms, the stakeholders, the objectives, the adopted technologies, the data properties and the obstacles. According to the year-wise analysis, it is found that no relevant primary study between 2010 and 2013 was found. This implies that the research of data analytics in agricultural sectors is a popular topic from recent years, so the results from before 2010 are likely less relevant. In total, 535 papers published from 2010 to 2020 were retrieved using both automatic and manual search strategies, among which 45 journal articles were selected for further analysis. From these primary studies, 33 features and 34 different obstacles were identified. The identified features and obstacles help characterize the different data analytics platforms and pave the way for further research.

Automated summary

This article presents the results of an in-depth systematic literature review on the characteristics and obstacles of data analytics platforms in the agricultural sector. The findings suggest that data analytics in agriculture has become increasingly important in recent years, and provide a foundation for further research.