Abstract
In recent years, the concept of Agriculture 4.0 has emerged as an evolution of precision agriculture (PA) through the diffusion of the Internet of things (IoT). There is a perception that the PA adoption is occurring at a slower pace than expected. Little research has been carried out about Agriculture 4.0, as well as to farmer behavior and operations management. This work explores what drives the adoption of PA in the Agriculture 4.0 context, focusing on farmer behavior and operations management. As a result of a multimethod approach, the factors explaining the PA adoption in the Agriculture 4.0 context and a model of irrigation operations management are proposed. Six simulation scenarios are performed to study the relationships among the factors involved in irrigation planning. Empirical findings contribute to a better understanding of what Agriculture 4.0 is and to expand the possibilities of IoT in the PA domain. This work also contributes to the discussion on Agriculture 4.0, thanks to multidisciplinary research bringing together the different perspectives of PA, IoT and operations management. Moreover, this research highlights the key role of IoT, considering the farmer’s possible choice to adopt several IoT sensing technologies for data collection.
Highlights
Agriculture is changing in recent years and, in the same way as the industry, is forced to modernize its work methodologies and to take advantage of opportunities offered by the Internet of things (IoT) [1]
This research seeks to contribute to filling these gaps by answering the following question: What drives the adoption of precision agriculture in the context of Agriculture 4.0, focusing on farmer behavior and operations management? To answer this question, this research aims to achieve the following objectives: exploring the factors that can affect the adoption of precision agriculture in the context of Agriculture 4.0; proposing a model to understand and formalize agricultural operations management based on identified factors; performing simulation scenarios, to study the relationships among the identified factors that allow the design of the model of agricultural operations management
The factors resulting from interviews with experts are described first, to continue with the factors resulting from case studies and with the proposition of a model of irrigation operations management using IDEF0
Summary
Agriculture is changing in recent years and, in the same way as the industry, is forced to modernize its work methodologies and to take advantage of opportunities offered by the Internet of things (IoT) [1]. IoT plays a key role in agriculture since the sensors can measure several quantities continuously, and by using the cloud processing power [7], it is possible to create models to evaluate the crop development and soil resources and water availability to support the decision-making process or even agriculture automation. Such models can evaluate evapotranspiration [8] or soil properties and their dynamics or even evaluate water demands in paddy areas. The IoT sensing technologies make room for innovative ways to better use natural resources like water in irrigation [9,10]
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