## 5 Development of the Models
### Organization of the Data  
To make a good representation with time series, a time interval must be chosen that captures in some way a descriptive behavior for the pattern to be analyzed. In econometrics, for example, this problem generally depends on the periodicity with which the data are obtained (monthly, annual, quarterly indices, etc.). In data traffic, each transmitted packet carries headers that provide information in an almost continuous manner, for which reason an interval must be chosen that yields global data. In general, noticeably short time intervals will show more specific behaviors, while very long periods will emphasize more global behaviors. In the case study presented, the traffic data generated by a system made up of nine sets of FC28 sensors coupled to the same number of ESP8266 development platforms interconnected with each other as shown in Figure 2. These connections were made through a wireless network with WiFi technology under the 802.11n standard that supplied the soil moisture data.  
Figure 3 shows the implementation of a real prototype of the ESP8226 sensor FC28 set for the measurement of humidity parameters in a small Colombian Creole potato crop.  
The distribution of the nine sensors was carried out homogeneously throughout the analyzed area of about 50 square meters. In this way, each sensor was always within a distance of no more than 50 m from the range of the WiFi gateway. The nine sensors were configured in different channels for the 2.4 GHz frequency band to avoid collisions in radio signals. In these environments with low radio frequency noise, signal losses were negligible, less than 1%. In general, all the signals measured between each sensor and the WiFi gateway had a low RSSI (Received Signal Strength Indicator) level. All measurements were below -50 dBm, which is an excellent signal level.  
Some of the factors that can attenuate the quality of the transmission over WiFi signals can be: High radio frequency noise, terrain horography, thickness of the crop, or the quality of the transmitting and receiving antennas. Rain and climatic and atmospheric conditions are factors that, in general, do not affect the transmission of signals below 10 GHz. However, sometimes it has been shown that these external conditions greatly affect the quality of connection 2.4 GHz networks. For this reason,  
Figure 3: Prototype of ESP8266 and Sensor FC-28 in potato cultivation.  
Figure 2: ESP8266-NodeMCU and Sensor FC-28 mounting diagram.  
the study of external conditions is a key factor when designing the appropriate configuration for a WSN system such as the one proposed in this study.  
Due to the periodic 3-min transmissions, approximately 200 samples were taken. Once the data were organized, they were stored in GRETL as a time series [27], with a frequency of 32 samples (seasonal frequency of the series obtained by calculating the average number of samples between peaks) and any starting reference since a daily, weekly, etc. index was not followed. They were then graphically represented to observe the evolution of the variable over time. Figure 4 shows the graphic representation of the original series.  
As can be seen, with the naked eye it is not possible to determine stationarity, since it does not present a clear trend or a defined variance. Therefore, the characteristics of the series must be analyzed in more depth.