Application Possibilities of IoT-based Management Systems in Agriculture

Mihály Tóth (), János Felföldi (), László Várallyai () and Róbert Szilágyi ()
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Mihály Tóth: Faculty of Economics and Business, University of Debrecen
János Felföldi: Faculty of Economics and Business, University of Debrecen
László Várallyai: Faculty of Economics and Business, University of Debrecen
Róbert Szilágyi: Faculty of Economics and Business, University of Debrecen

A chapter in Information and Communication Technologies for Agriculture—Theme II: Data, 2022, pp 77-102 from Springer

Abstract: Abstract The optimization of agricultural production and business processes is a crucial task in order to fulfill the demand of the increasing population, to meet quality requirements, to reduce the environmental impact as well as to improve economic efficiency. The Industry 4.0 concept provides various methods in this regard, including data acquisition based on IoT (Internet of Things), or data analytics based on Big Data, to support the decision-making process of the management and the data requirement of process control methods. During preliminary research, several modular data acquisition systems, as well as management applications have been developed based on a production system to measure various environmental factors at multiple spatial points. Considering the experience gained from the testing sessions, there was a need for further development regarding the end-user perspective in order to substantiate the practical application. A comparative research was required, considering previous experience and the literature of data acquisition systems, used in agriculture. The comparison concerned an own iteration of a production system and other systems, developed by researchers of the field, to examine different options and directions. Considering three important factors, the focus was on the data acquisition systems, data management, and data utilization methods. The comparison begins with a quantitative bibliometric analysis, determining the field and characteristic connections using network and cluster analysis, considering the IoT concept as the central element. Subsequently, the progression of a system and its evaluation is presented, performed in a greenhouse. This iteration highly focuses on data management with the modification of the existing infrastructure by integrating the Hadoop ecosystem to achieve a standardized interface.

Keywords: Data acquisition; IoT; Sensor network; Decision support; Agriculture (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/978-3-030-84148-5_4

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