# Digital Transformation of Beekeeping through the Use of a Decision Making Architecture
## 1 Introduction
To allow humans and software to communicate between them, standard interfaces have been developed. The use of data coming from sensors or from the network is supported by this software. They have storage and processing abilities. Agriculture systems have the same challenges as those encountered by manufacturing systems. Theses challenges are related to their sizing, to the understanding of their mechanisms, to the improvement of their productivity, and to their performance evaluation. Theses challenges produce difficulties to make decisions for all the actors in the agriculture systems. Digitalization processes are currently being increasingly introduced into various sectors of the national economy, including the agricultural sector [4]. Digital Transformation (DT) refers to the combination of digital technology and areas of the business to finally realize the transformation of the management model and business model [5]. Indeed, DT is often referred to either as evolution, or the creation of entire new business models in companies or business sectors [6]. Digitalization can be considered as part of DT [7]. It describes socio-technical processes and their impacts on human activities that result from the use of interconnected digital technologies [8]. DT is a convergence of hard (technology) and soft (people and businesses) forces and movements from which additional value emerges [9]. According to the authors, one of the disruptive technologies adopted in DT implementations is \"IoT connected devices\". In the same way, the following categories were used for coding the DT [10]: _Technologies, Management/Processes_, and _People_. The authors also list the elements within each category. Among these elements, in this paper, we meanly use IoT (_Technology_) in order to create new services and products (_Management/Processes_) for workforce, stakeholders, and partners (_People_). Thus, our process respects the properties of the DT, with an implementation in beekeeping. As new services, we focus on the development of decision support systems. This new service allows us to improve the business models of the different actors and to help save the bees. In our context, we depict a new approach to apply the DT in the beekeeping sectors and help the actors of this area to make their decisions. To this end, different proposals are made:  
* A proposal of Maturity Model (MM) Levels for smart beehives;
* A proposal for analysing all the decisions that can be made in the beekeeping sectors using spatio-temporal matrix;
* A proposal of generic architecture that corresponds to the decisions analysed in the matrix. The paper is structured as follows: Section 2 presents a synthetic review of work about smart agriculture and more specifically on beekeeping with a focus on IoT. Section 3 proposes a Maturity Model to categorize the digital maturity of smart beehive systems and presents classification of the literature on smart beehives following this Maturity Model. Section 4 depicts a spatio-temporal matrix to analyse the possible decision-making on smart beehives. Section 5 explains the global view and the generic architecture for the proposed smart beehives. An implementation is shown in the Section 6. Finally, Section 7 presents the conclusions and perspectives.