## 1 Introduction
### State-of-the-Art
For the development of this research, they inoculated these bacteria: six _Bacillus_ sp., B10, B25, B157, B175, B205, and B281, and one _Pseudomonas_ sp., P286, which help to detect and control CLR in \begin{table}
\begin{tabular}{c c} \hline \hline
**Kind of Variable** & **Relevance** \\ \hline Climate variation (Altitude and rainfall) & High \\ Soil components & Medium–low \\ Cropping practices & Medium \\ Coffee tree productive characteristics & High \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Kinds of variables that describe the importance of coffee plots in the presence of CLR [29]. Figure 4: CLR development stages [28]. the early development stages, according to a preliminary result presented by [PERSON] et al. (2007). For the experiment, two important coffee varieties, Mundo Novo and Catuai, were selected due to the high susceptibility to CLR. Therefore, for three years, the varieties with the disease interacted with different treatments (bacteria) to analyze the behavior evolution between them. Based on the results of the treatments, the isolates P286 and B157 were as efficient as the copper fungicide in controlling the rust. Hence, considering the harmful effects due to the copper fungicide, the application of biological control with the B157 isolate of _Bacillus_ sp. may be a reliable alternative solution to CLR management. That is why this research displayed the opportunity to successfully biocontrol CLR, for specialty coffee growers. [PERSON] et al. [31], in 2012, proposed as well a biological detection and control based on a fungus, _Lecanicillium lecanii_. Their primary interest in the crops, in general, was the analogy of the coexistence of organisms in a specific environment with defined conditions that encounter a perfect balance. Given the above, the biological control system of the _A. instabilis_ ants were mutualistically associated with the white halos of the fungus, _Lecanicillium lecanii_, based on the CLR effect. However, the hypothesis stated the possibility that spores from _Lecanicillium lecanii_ help to attack the _Hemileia vastatrix_ before the rainy season. The effect of the time delay of _Lecanicillium lecanii_ in _Hemileia vastatrix_ resulted in a relationship between the two fungi and the ants not to be demonstrated, in spite of the control experiment resembling the real world. In conclusion, the restriction of biotic factors directly affects the development of CLR; therefore, for future work, it is important to consider the climate variation of an ecosystem to be able to predict such development [31]. (iv) Wireless Sensor Networks (WSN)  
Wireless Sensor Networks (WSN) are a technology that is being used in many countries worldwide to monitor different agricultural characteristics in real time and remotely. It consists of multiple non-assisted embedded devices, called sensor nodes, that collect data in the field and communicate them wirelessly to a centralized processing station, which is known as the Base Station (BS). The BS has data storage, data processing, and data fusion capabilities, and it is in charge of transmitting the received data to the Internet to present them to an end-user [32]. Once the collected data are stored on a central server on the Internet, further analysis, processing, and visualization techniques are applied to extract valuable information and hidden correlations, which can help to detect changes in crop characteristics. These changes could be used as indicators of phytosanitary problems such as nutritional deficiencies, pests, diseases, and water stress. WSN is a powerful technology since the information of remote and inaccessible physical environments can be easily accessed through the Internet, with the help of the cooperative and constant monitoring of multiple sensors [33]. The sensor nodes in a WSN setup can vary in terms of their functions. Some of them can serve as simple data collectors that monitor a single physical phenomenon, while more powerful nodes may also perform more complex processing and aggregation operations.