Smart farming in agricultural industry: Mobile technology perspective

Abstract

The aim of this research is to examine key indicators that are necessary for the implementation and development of smart farming concepts in the agricultural industry, especially from the applied mobile technology point of view. Accordingly, the authors used a neural network based software solution to determine the correlation, relationship structure and partial contribution of indicators for the mobile technology development in agricultural industries in selected countries. The validity of the input-output model in a neural network based software solution was evaluated using the Minkowski error and Quasi-Newton method through several iterations/epochs. The neural network structure has shown the importance of particular indicators for adopting a mobile technology perspective in the agricultural industry, where the application of Information and Communications Technologies (ICT) in agriculture is most emphasized. Only those countries that invest the most in the ICT in the agricultural sector can achieve greater efficiency and productivity by applying smart farming.

Keywords

• smart farming
• agricultural industry
• mobile technology
• agricultural information systems
• neural networks